Interpolation error minimization for data reduction
First Claim
1. A method of adjusting a series of N subset data points into best fit data points for a series of sample data points that form a data source, comprising:
- identifying M segments having endpoints defined by adjacent subset data points, wherein M equals N−
1; and
performing an iterative process, including;
determining a linear interpolation error for each of the M segments;
selecting a target segment (STARGET) from the segments; and
reducing the interpolation error for STARGET by moving one endpoint of STARGET by an increment corresponding to at least one sample data point in the series of sample data points to shorten STARGET.
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Abstract
Systems and methods are provided for reducing a set of data points into a subset of best fit data points. According to one aspect, a method of adjusting a series of N data points into best fit data points for a set of sample data points that form a data source is provided. According to this method, M segments are identified, wherein M equals N−1. Each segment has endpoints defined by adjacent subset data points. An iterative process is performed that includes determining a linear interpolation error for each of the M segments, selecting a target segment (STARGET) from the segments, and reducing the interpolation error for STARGET by moving one endpoint of STARGET by an increment corresponding to at least one sample data point in the series of sample data points to shorten STARGET. Other methods and systems are provided herein.
26 Citations
126 Claims
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1. A method of adjusting a series of N subset data points into best fit data points for a series of sample data points that form a data source, comprising:
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identifying M segments having endpoints defined by adjacent subset data points, wherein M equals N−
1; and
performing an iterative process, including;
determining a linear interpolation error for each of the M segments;
selecting a target segment (STARGET) from the segments; and
reducing the interpolation error for STARGET by moving one endpoint of STARGET by an increment corresponding to at least one sample data point in the series of sample data points to shorten STARGET. - View Dependent Claims (2, 3, 4, 5)
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6. A method of adjusting a series of N data points into best fit data points for a series of sample data points that form a data source, comprising:
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identifying M segments having endpoints defined by adjacent subset data points, wherein M equals N−
1; and
performing an iterative process, including;
determining a linear interpolation error for each of the M segments;
selecting a target segment (STARGET) from the segments;
determining whether there is a first adjacent segment (S1ST) having a common endpoint with STARGET such that S1ST has endpoints defined by a first data point (PS+1) and a second data point (PS);
determining whether there is a second adjacent segment (S2ND) having a common endpoint with STARGET such that S2ND has endpoints defined by a first data point (PS+1) and a second data point (PS+2);
upon determining that there is no S1ST, moving PS+1 by an increment corresponding to at least one sample data point in the series of sample data points to shorten STARGET and lengthen S2ND; and
upon determining that there is no S2ND, moving PS by an increment corresponding to at least one sample data point in the series of sample data points to shorten STARGET and lengthen S1ST. - View Dependent Claims (7, 8, 9)
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10. A method of adjusting a series of N subset data points into best fit data points for a series of sample data points that form a data source, comprising:
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identifying M segments having endpoints defined by adjacent subset data points, wherein M equals N−
1; and
performing an iterative process, including;
determining a linear interpolation error for each of the M segments;
selecting a target segment (STARGET) from the segments; and
determining whether there is a first adjacent segment (S1ST) having a common endpoint with STARGET such that S1ST has endpoints defined by a first data point (PS−
1) and a second data point (PS);
determining whether there is a second adjacent segment (S2ND) having a common endpoint with STARGET such that S2ND has endpoints defined by a first data point (PS+1) and a second data point (PS+2);
upon determining that there is a S1ST and a S2ND, determining whether an interpolation error for S1ST (ES1ST) or an interpolation error for S2ND (ES2ND) is larger;
upon determining that ES1ST is larger than ES2ND, moving PS+1 by an increment corresponding to at least one sample data point in the series of sample data points to shorten STARGET and lengthen S2ND; and
upon determining that ES2ND is larger than ES1ST, moving PS by an increment corresponding to at least one sample data point in the series of sample data points to shorten STARGET and lengthen S1ST. - View Dependent Claims (11, 12, 13)
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14. A method of adjusting a series of N subset data points into best fit data points for a series of sample data points that form a data source, comprising:
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identifying M segments having endpoints defined by adjacent subset data points, wherein M equals N−
1; and
performing an iterative process, including;
determining a linear interpolation error for each of the M segments;
selecting a target segment (STARGET) from the segments;
determining whether there is a first adjacent segment (S1ST) having a common endpoint with STARGET such that S1ST has endpoints defined by a first data point (PS−
1) and a second data point (PS);
determining whether there is a second adjacent segment (S2ND) having a common endpoint with STARGET such that S2ND has endpoints defined by a first data point (PS+1) and a second data point (PS+2);
upon determining that there is a S1ST and a S2ND, determining whether an interpolation error for S1ST (ES1ST) or an interpolation error for S2ND (ES2ND) is larger;
upon determining that ES1ST is larger than ES2ND, moving PS+1 by an increment corresponding to at least one sample data point in the series of sample data points to shorten STARGET and lengthen S2ND;
upon determining that ES2ND is larger than ES1ST, moving PS by an increment corresponding to at least one sample data point in the series of sample data points to shorten STARGET and lengthen S1ST, upon determining that there is no S1ST, moving PS+1 by an increment corresponding to at least one sample data point in the series of sample data points to shorten STARGET and lengthen S2ND; and
upon determining that there is no S2ND, moving PS by an increment corresponding to at least one sample data point in the series of sample data points to shorten STARGET and lengthen S1ST. - View Dependent Claims (15, 16)
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17. A method of reducing linear interpolation error for a data subset that contains a series of data points from a data source, comprising:
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identifying a target segment (STARGET) having endpoints defined by a first data point (PS) and a second data point (PS+1);
determining whether there is a first adjacent segment (S1ST) having a common endpoint with STARGET such that S1ST has endpoints defined by a first data point (PS−
1) and a second data point (PS);
determining whether there is a second adjacent segment (S2ND) having a common endpoint with STARGET such that S2ND has endpoints defined by a first data point (PS+1) and a second data point (PS+2);
upon determining that there is no S1ST, moving PS+1 by an increment corresponding to at least one data point in the series of data points to shorten STARGET and lengthen S2ND; and
upon determining that there is no S2ND, moving PS by an increment corresponding to at least one data point in the series of data points to shorten STARGET and lengthen S1ST. - View Dependent Claims (18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28)
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29. A method of reducing linear interpolation error for a data subset that contains a series of data points from a source data, comprising:
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identifying a target segment (STARGET) having endpoints defined by a first data point (PS) and a second data point (PS+1);
determining whether there is a first adjacent segment (S1ST) having a common endpoint with STARGET such that S1ST has endpoints defined by a first data point (PS−
1) and a second data point (PS);
determining whether there is a second adjacent segment (S2ND) having a common endpoint with STARGET such that S2ND has endpoints defined by a first data point (PS+1) and a second data point (PS+2);
upon determining that there is a S1ST and a S2ND, determining whether an interpolation error for S1ST (ES1ST) or an interpolation error for S2ND (ES2ND) is larger;
upon determining that ES1ST is larger than ES2ND, moving PS+1 by an increment corresponding to at least one data point in the series of data points to shorten STARGET and lengthen S2ND; and
upon determining that ES2ND is larger than ES1ST, moving PS by an increment corresponding to at least one data point in the series of data points to shorten STARGET and lengthen S1ST - View Dependent Claims (30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40)
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41. A method of reducing linear interpolation error for a data subset that contains a series of data points from a source data, comprising:
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identifying a target segment (STARGET) having endpoints defined by a first data point (PS) and a second data point (PS+1);
determining whether there is a first adjacent segment (S1ST) having a common endpoint with STARGET such that S1ST has endpoints defined by a first data point (PS−
1) and a second data point (PS);
determining whether there is a second adjacent segment (S2ND) having a common endpoint with STARGET such that S2ND has endpoints defined by a first data point (PS+1) and a second data point (PS+2);
upon determining that there is no S1ST, moving PS+1 by an increment corresponding to at least one data point in the series of data points to shorten STARGET and lengthen S2ND;
upon determining that there is no S2ND, moving PS by an increment corresponding to at least one data point in the series of data points to shorten STARGET and lengthen S1ST;
upon determining that there is a S1ST and a S2ND, determining whether an interpolation error for S1ST (ES1ST) or an interpolation error for S2ND (ES2ND) is larger;
upon determining that ES1ST is larger than ES2ND, moving PS+1 by an increment corresponding to at least one data point in the series of data points to shorten STARGET and lengthen S2ND; and
upon determining that ES2ND is larger than ES1ST, moving PS by an increment corresponding to at least one data point in the series of data points to shorten STARGET and lengthen S1ST. - View Dependent Claims (42, 43, 44, 45, 46)
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47. A method of reducing linear interpolation error for a data subset that contains a plurality of data points from source data, wherein the data points from the source data are sequenced from left to right, the method comprising:
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identifying a target segment (STARGET) having endpoints defined by a left data point (PL) and a right data point (PR);
determining whether there is a left segment (SLEFT) with respect to STARGET having endpoints defined by a left data point (PL−
1) and a right data point (PL);
determining whether there is a right segment (SRIGHT) with respect to STARGET having endpoints defined by a left data point (PR) and a right data point (PR+1);
upon determining that there is no SLEFT, shortening STARGET by moving PR left by an increment corresponding to at least one data point in the series of data points;
upon determining that there is no SRIGHT, shortening STARGET by moving PL right by an increment corresponding to at least one data point in the series of data points;
upon determining that there is a SLEFT and a SRIGHT, determining whether an interpolation error for SLEFT (ESLEFT) or an interpolation error for SRIGHT (ESRIGHT) is larger;
upon determining that ESLEFT is larger than ESRIGHT, moving PR left by an increment corresponding to at least one data point in the series of data points to shorten STARGET and lengthen SRIGHT; and
upon determining that ESRIGHT is larger than ESLEFT, moving PL right by an increment corresponding to at least one data point in the series of data points to shorten STARGET and lengthen SLEFT. - View Dependent Claims (48, 49, 50, 51, 52)
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53. A method of selecting best fit data points for a series of sample data points that form source data, comprising:
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seeding a series of N data points on the source data; and
performing an iterative process, including;
determining linear interpolation errors between the N data points and the source data for M segments that are capable of being formed between adjacent data points, wherein M equals N−
1;
sorting the M segments based on linear interpolation error size;
identifying a target segment (STARGET) from the M segments; and
reducing the linear interpolation error for STARGET by moving one endpoint of STARGET by an increment corresponding to at least one sample data point in the series of sample data points to shorten STARGET. - View Dependent Claims (54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64)
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65. A method of selecting best fit data points for a data subset of a sequence of sample data points that form source data, comprising:
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seeding a series of N data points on the source data;
determining linear interpolation errors between the N data points and the source data for M segments that are capable of being formed between adjacent data points, wherein M equals N−
1;
sorting the M segments based on linear interpolation error size;
identifying a target segment (STARGET) from the M segments; and
reducing the linear interpolation error for STARGET, including;
determining whether there is a first adjacent segment (S1ST) having a common endpoint with STARGET such that S1ST has endpoints defined by a first data point (PS−
1) and a second data point (PS);
determining whether there is a second adjacent segment (S2ND) having a common endpoint with STARGET such that S2ND has endpoints defined by a first data point (PS+1) and a second data point (PS+2);
upon determining that there is a S1ST and a S2ND, determining whether an interpolation error for S1ST (ES1ST) or an interpolation error for S2ND (ES2ND) is larger;
upon determining that ES1ST is larger than ES2ND, moving PS+1 by an increment corresponding to at least one data point in the sequence of sample data points to shorten STARGET and lengthen S2ND; and
upon determining that ES2ND is larger than ES1ST, moving PS by an increment corresponding to at least one data point in the sequence of sample data points to shorten STARGET and lengthen S1ST - View Dependent Claims (66, 67, 68, 69, 70, 71, 72)
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73. A method of selecting best fit data points from a sequence of sample data points that form source data, comprising:
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seeding a series of N data points on the source data;
determining linear interpolation errors between the N data points and the source data for M segments that are capable of being formed between adjacent data points, wherein M equals N−
1;
sorting the M segments based on linear interpolation error size;
identifying a target segment (STARGET) from the M segments; and
reducing the linear interpolation error for STARGET, including;
determining whether there is a left segment (SLEFT) with respect to STARGET having endpoints defined by a left data point (PL−
1) and a right data point (PL);
determining whether there is a right segment (SRIGHT) with respect to STARGET having endpoints defined by a left data point (PR) and a right data point (PR+1);
upon determining that there is no SLEFT, shortening STARGET by moving PR left by an increment corresponding to at least one data point in the sequence of sample data points;
upon determining that there is no SRIGHT, shortening STARGET by moving PL right by an increment corresponding to at least one data point in the sequence of sample data points;
upon determining that there is a SLEFT and a SRIGHT, determining whether an interpolation error for SLEFT (ESLEFT) or an interpolation error for SRIGHT (ESRIGHT) is larger;
upon determining that ESLEFT is larger than ESRIGHT, moving PR left by an increment corresponding to at least one data point in the sequence of sample data points to shorten STARGET and lengthen SRIGHT; and
upon determining that ESRIGHT is larger than ESLEFT, moving PL right by an increment corresponding to at least one data point in the sequence of sample data points to shorten STARGET and lengthen SLEFT. - View Dependent Claims (74, 75, 76, 77)
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78. A method of reducing a series of characterization data points from a characterization source data into a data subset for a model table by selecting best fit data points to reduce the linear interpolation error in a simulation model, comprising:
-
seeding a series of N data points on the characterization source data;
identifying M segments having endpoints defined by adjacent data points, wherein M equals N−
1;
determining a linear interpolation error for each of the M segments;
selecting a target segment (STARGET) from the segments; and
reducing the interpolation error for STARGET by moving one endpoint of STARGET by an increment corresponding to at least one data point in the series of characterization data points to shorten STARGET. - View Dependent Claims (79, 80, 81, 82)
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83. A method of reducing a series of characterization data points from a characterization source data into a data subset for a model table by selecting best fit data points to reduce the linear interpolation error in a simulation model, comprising:
-
seeding a series of N data points on the characterization source data;
identifying M segments having endpoints defined by adjacent subset data points, wherein M equals n−
1; and
performing an iterative process, including;
determining a linear interpolation error for each of the M segments;
selecting a target segment (STARGET) from the segments;
determining whether there is a first adjacent segment (S1ST) having a common endpoint with STARGET such that S1ST has endpoints defined by a first data point (PS−
1) and a second data point (PS);
determining whether there is a second adjacent segment (S2ND) having a common endpoint with STARGET such that S2ND has endpoints defined by a first data point (PS+1) and a second data point (PS+2);
upon determining that there is a S1ST and a S2ND, determining whether an interpolation error for S1ST (ES1ST) or an interpolation error for S2ND (ES2ND) is larger;
upon determining that ES1ST is larger than ES2ND, moving PS+1 to shorten STARGET and lengthen S2ND by an increment corresponding to at least one data point in the series of characterization data points; and
upon determining that ES2ND is larger than ES1ST, moving PS to shorten STARGET and lengthen S1ST by an increment corresponding to at least one data point in the series of characterization data points. - View Dependent Claims (84, 85)
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86. A method of reducing a series of characterization data points from characterization source data into a data subset for a model table by selecting best fit data points to reduce the linear interpolation error in a simulation model, comprising:
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seeding a series of N data points on the characterization source data;
performing an iterative process to identify best fit data points, including;
determining linear interpolation errors between the N data points and the source data for M segments that are capable of being formed between adjacent data points, wherein M equals N−
1;
sorting the M segments based on linear interpolation error size;
identifying a target segment (STARGET) from the M segments; and
reducing the linear interpolation error for STARGET, including;
determining whether there is a first adjacent segment (S1ST) having a common endpoint with STARGET such that S1ST has endpoints defined by a first data point (PS−
1) and a second data point (PS);
determining whether there is a second adjacent segment (S2ND) having a common endpoint with STARGET such that S2ND has endpoints defined by a first data point (PS+1) and a second data point (PS+2);
upon determining that there is a S1ST and a S2ND, determining whether an interpolation error for S1ST (ES1ST) or an interpolation error for S2ND (ES2ND) is larger;
upon determining that ES1ST is larger than ES2ND, moving PS+1 to shorten STARGET and lengthen S2ND by an increment corresponding to at least one data point in the series of characterization data points; and
upon determining that ES2ND is larger than ES1ST, moving PS by an increment corresponding to at least one data point in the series of characterization data points to shorten STARGET and lengthen S1ST, extracting the best fit data points upon completion of the iterative process; and
incorporating the best fit data points as the data subset for the simulation model table. - View Dependent Claims (87, 88)
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89. A method of forming simulation model tables, comprising:
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retrieving source data from cell libraries, the source data including a series of sample data points;
compressing the source data into subsets of best fit data points, including;
identifying M segments having endpoints defined by adjacent subset data points, wherein M equals N−
1; and
performing an iterative process, including;
determining a linear interpolation error for each of the M segments;
selecting a target segment (STARGET) from the segments; and
reducing the interpolation error for STARGET by moving one endpoint of STARGET by an increment of at least one sample point in the series of sample data points to shorten STARGET; and
incorporating the subsets into simulation model tables. - View Dependent Claims (90, 91, 92, 93)
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94. A method of forming simulation model tables, comprising:
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retrieving source data from cell libraries, the source data including a series of sample data points;
compressing the source data into subsets of best fit data points, including;
identifying M segments having endpoints defined by adjacent subset data points, wherein M equals N−
1; and
performing an iterative process, including;
determining a linear interpolation error for each of the M segments;
selecting a target segment (STARGET) from the segments;
determining whether there is a first adjacent segment (S1ST) having a common endpoint with STARGET such that S1ST has endpoints defined by a first data point (PS−
1) and a second data point (PS);
determining whether there is a second adjacent segment (S2ND) having a common endpoint with STARGET such that S2ND has endpoints defined by a first data point (PS+1) and a second data point (PS+2);
upon determining that there is no S1ST, moving PS+1 by an increment corresponding to at least one sample data point in the series of sample data points to shorten STARGET and lengthen S2ND; and
upon determining that there is no S2ND, moving PS by an increment corresponding to at least one sample data point in the series of sample data points to shorten STARGET and lengthen S1ST; and
incorporating the subsets in to simulation model tables. - View Dependent Claims (95, 96, 97)
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98. A method of forming simulation model tables, comprising:
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retrieving source data from cell libraries, the source data including a series of sample data points;
compressing the source data into subsets of best fit data points, including;
identifying M segments having endpoints defined by adjacent subset data points, wherein M equals N−
1; and
performing an iterative process, including;
determining a linear interpolation error for each of the M segments;
selecting a target segment (STARGET) from the segments; and
determining whether there is a first adjacent segment (S1ST) having a common endpoint with STARGET such that S1ST has endpoints defined by a first data point (PS−
1) and a second data point (PS);
determining whether there is a second adjacent segment (S2ND) having a common endpoint with STARGET such that S2ND has endpoints defined by a first data point (PS+1) and a second data point (PS+2);
upon determining that there is a S1ST and a S2ND, determining whether an interpolation error for S1ST (ES1ST) or an interpolation error for S2ND (ES2ND) is larger;
upon determining that ES1ST is larger than ES2ND, moving PS+1 by an increment corresponding to at least one sample data point in the series of sample data points to shorten STARGET and lengthen S2ND; and
upon determining that ES2ND is larger than ES1ST, moving PS by an increment corresponding to at least one sample data point in the series of sample data points to shorten STARGET and lengthen S1ST; and
incorporating the subsets in to simulation model tables. - View Dependent Claims (99, 100, 101)
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102. A method of forming simulation model tables, comprising:
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retrieving source data from cell libraries, the source data including a series of sample data points;
compressing the source data into subsets of best fit data points, including;
identifying M segments having endpoints defined by adjacent subset data points, wherein M equals N−
1; and
performing an iterative process, including;
determining a linear interpolation error for each of the M segments;
selecting a target segment (STARGET) from the segments;
determining whether there is a first adjacent segment (S1ST) having a common endpoint with STARGET such that S1ST has endpoints defined by a first data point (PS−
1) and a second data point (PS);
determining whether there is a second adjacent segment (S2ND) having a common endpoint with STARGET such that S2ND has endpoints defined by a first data point (PS+1) and a second data point (PS+2);
upon determining that there is a S1ST and a S2ND, determining whether an interpolation error for S1ST (ES1ST) or an interpolation error for S2ND (ES2ND) is larger;
upon determining that ES1ST is larger than ES2ND, moving PS+1 by an increment corresponding to at least one sample data point in the series of sample data points to shorten STARGET and lengthen S2ND;
upon determining that ES2ND is larger than ES1ST, moving PS by an increment corresponding to at least one sample data point in the series of sample data points to shorten STARGET and lengthen S1ST;
upon determining that there is no S1ST, moving PS+1 by an increment corresponding to at least one sample data point in the series of sample data points to shorten STARGET and lengthen S2ND; and
upon determining that there is no S2ND, moving PS by an increment corresponding to at least one sample data point in the series of sample data points to shorten STARGET and lengthen S1ST. - View Dependent Claims (103, 104)
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105. A method of designing a circuit, comprising:
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providing libraries of source data, the source data including a series of sample data points;
compressing the libraries into subsets of best fit data points for simulation model tables, including;
retrieving source data from cell libraries;
compressing the source data into subsets of best fit data points, including;
identifying M segments having endpoints defined by adjacent subset data points, wherein M equals N−
1; and
performing an iterative process that includes determining a linear interpolation error for each of the M segments, selecting a target segment (STARGET) from the segments; and
reducing the interpolation error for STARGET by an increment corresponding to at least one sample data point in the series of sample data points; and
incorporating subsets into simulation model tables; and
designing high level circuit using the simulation model tables. - View Dependent Claims (106, 107, 108)
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109. A system, comprising:
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a processor;
computer readable medium coupled to the processor, wherein the computer readable medium is encoded with a computer program for reducing linear interpolation error between a series of data points in a data subset and source data, the source data including a series of sample data points, wherein the computer readable medium includes;
programming code for identifying a target segment (STARGET) having endpoints defined by a first data point (PS) and a right data point (PS+1);
programming code for determining whether there is a first adjacent segment (S1ST) having a common endpoint with STARGET such that S1ST has endpoints defined by a first data point (PS−
1) and a second data point (PS);
programming code for determining whether there is a second adjacent segment (S2ND) having a common endpoint with STARGET such that S2ND has endpoints defined by a first data point (PS+1) and a second data point (PS+2);
programming code for, upon determining that there is a S1ST and a S2ND, determining whether an interpolation error for S1ST (ES1ST) or an interpolation error for S2ND (ES2ND) is larger;
programming code for, upon determining that ES1ST is larger than ES2ND, moving PS+1 by an increment corresponding to at least one sample data point in the series of sample data points to shorten STARGET and lengthen S2ND; and
programming code for, upon determining that ES2ND is larger than ES1ST, moving PS by an increment corresponding to at least one sample data point in the series of sample data points to shorten STARGET and lengthen S1ST. - View Dependent Claims (110, 111, 112, 113, 114, 115, 116)
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117. A cell characterization system, comprising:
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a processor;
computer readable medium coupled to the processor, wherein the computer readable medium is encoded with a computer program for extracting best fit data points from a cell characterization source data for modeling of a cell using linear interpolation, the source data including a series of sample data points, wherein the computer readable medium includes;
programming code for seeding a series of N data points on the characterization source data;
programming code for performing an iterative process to identify best fit data points, including;
programming code for determining linear interpolation errors between the N data points and the source data for M segments that are capable of being formed between adjacent data points, wherein M equals N−
1;
programming code for sorting the M segments based on linear interpolation error size;
programming code for identifying a target segment (STARGET) from the M segments; and
programming code for reducing the linear interpolation error for STARGET, including;
programming code for determining whether there is a first adjacent segment (S1ST) having a common endpoint with STARGET such that S1ST has endpoints defined by a first data point (PS−
1) and a second data point (PS);
programming code for determining whether there is a second adjacent segment (S2ND) having a common endpoint with STARGET such that S2ND has endpoints defined by a first data point (PS+1) and a second data point (PS+2);
programming code for, upon determining that there is a S1ST and a S2ND, determining whether an interpolation error for S1ST (ES1ST) or an interpolation error for S2ND (ES2ND) is larger;
programming code for, upon determining that ES1ST is larger than ES2ND, moving PS+1 by an increment corresponding to at least one sample data point in the series of sample data points to shorten STARGET and lengthen S2ND; and
programming code for, upon determining that ES2ND is larger than ES1ST, moving PS by an increment corresponding to at least one sample data point in the series of sample data points to shorten STARGET and lengthen S1ST;
programming code for extracting the best fit data points upon completion of the iterative process; and
programming code for incorporating the best fit data points as the data subset for the simulation model table. - View Dependent Claims (118, 119)
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120. A cell characterization system, comprising:
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a processor;
computer readable medium coupled to the processor, including;
a first memory storage for storing cell characterization source data that includes a series of sample data points;
a second memory storage for storing a data subset for a simulation model table; and
a third memory storage for storing a program for extracting best fit data points from a cell characterization source data for modeling of a cell using linear interpolation, wherein the memory storage includes;
programming code for seeding a series of N data points on the cell characterization source data;
programming code for identifying M segments having endpoints defined by adjacent data points, wherein M equals N−
1;
programming code for determining a linear interpolation error for each of the M segments;
programming code for selecting a target segment (STARGET) from the segments; and
programming code for reducing the interpolation error for STARGET by moving one endpoint of STARGET by an increment corresponding to at least one sample data point in the series of sample data points to shorten STARGET. - View Dependent Claims (121, 122, 123)
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124. A cell characterization system, comprising:
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a processor;
computer readable medium coupled to the processor, including;
a first memory storage for storing cell characterization source data that includes a series of sample data points;
a second memory storage for storing a data subset for a simulation model table; and
a third memory storage for storing a program for extracting best fit data points from a cell characterization data source for modeling of a cell using linear interpolation, wherein the memory storage includes;
programming code for seeding a series of N data points on the characterization source data;
programming code for performing an iterative process to identify best fit data points, including;
programming code for determining linear interpolation errors between the N data points and the source data for M segments that are capable of being formed between adjacent data points, wherein M equals N−
1;
programming code for sorting the M segments based on linear interpolation error size;
programming code for identifying a target segment (STARGET) from the M segments; and
programming code for reducing the linear interpolation error for STARGET, including;
programming code for determining whether there is a first adjacent segment (S1ST) having a common endpoint with STARGET such that S1ST has endpoints defined by a first data point (PS−
1) and a second data point (PS);
programming code for determining whether there is a second adjacent segment (S2ND) having a common endpoint with STARGET such that S2ND has endpoints defined by a first data point (PS+1) and a second data point (PS+2);
programming code for, upon determining that there is a S1ST and a S2ND, determining whether an interpolation error for S1ST (ES1ST) or an interpolation error for S2ND (ES2ND) is larger;
programming code for, upon determining that ES1ST is larger than ES2ND, moving PS+1 by an increment corresponding to at least one sample data point in the series of sample data points to shorten STARGET and lengthen S2ND; and
programming code for, upon determining that ES2ND is larger than ES1ST, moving PS by an increment corresponding to at least one sample data point in the series of sample data points to shorten STARGET and lengthen S1ST;
programming code for extracting the best fit data points upon completion of the iterative process; and
programming code for incorporating the best fit data points as the data subset for the simulation model table. - View Dependent Claims (125, 126)
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Specification