Analog to digital conversion using correlated quantization and collective optimization
First Claim
1. A nonstandard analog-to-digital converter for converter a sampled analog signal u, having N samples u1, . . . , uN each with a value between a first and a second level, into a digital signal x, having N corresponding 1-bit binary values x1, . . . , xN, such that a distortion measure d=(Au-Bx)T (Au-Bx) is minimized, where u and x are N-dimensional vectors, A and B are N×
- N matrices, and N is an integer greater than 1, the converter comprising;
N nonlinear amplifying means A1, . . . , AN, each having an output terminal supplying an output signal and input means operatively coupled to receive the output signals supplied by other amplifying means, one or more of the analog signal samples and a respective constant signal, the input means for taking the weighted sum of the signals received thereby, including applying respective weighting factors to the received signals, and providing the weighted sum to the amplifying means, wherein for any two of the N amplifying means Ai and Aj, where i and j are independent integers having values i=1, 2, . . . N and j=1, 2, . . . , N, the weighting factor Wij applied by the input means of Ai to the output signal supplied by Aj is the element of the ith row and jth column of a matrix -BT B, the weighting factor Kij applied by the input means of Ai to analog signal example uj is the element of the ith row and jth column of a matrix BT, the constant signal Ii received by the input means of Ai is the element of the ith row and ith column of the matrix -BT B, and the output signal supplied by Ai operatively stabilizes to binary value xi of the digital signal x.
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Abstract
A 1-bit nonstandard A/D converter for converting a block u of N samples of a continuous time analog signal u(t) into N corresponding 1-bit binary values x, such that a distortion measure of the form d(u,x)=(Au-Bx)T (Au-Bx) is minimized, is implemented with an N-input parallel sample-and-hold circuit and a neural network having N nonlinear amplifiers, where u and x are n-dimensional vectors, and A and B are N×N matrices. Minimization of the above distortion measure is equivalent to minimizing the quantity
1/2x.sup.T B.sup.T Bx-u.sup.T A.sup.T Bx,
which is achieved to at least a good approximation by the N-amplifier neural network. Accordingly, the conductances of the feedback connections among the amplifiers are defined by respective off-diagonal elements of the matrix -BT B. Additionally, each amplifier of the neural network is connected to receive the analog signal samples through respective conductances defined by the matrix BT. Furthermore, each amplifier receives a respective constant signal defined by the diagonal elements of the matrix -BT B. The stabilized outputs of the N amplifiers are the binary values of the digital signal x.
A multiple-bit nonstandard A/D converter based on for foregoing 1-bit A/D converter is also disclosed.
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Citations
32 Claims
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1. A nonstandard analog-to-digital converter for converter a sampled analog signal u, having N samples u1, . . . , uN each with a value between a first and a second level, into a digital signal x, having N corresponding 1-bit binary values x1, . . . , xN, such that a distortion measure d=(Au-Bx)T (Au-Bx) is minimized, where u and x are N-dimensional vectors, A and B are N×
- N matrices, and N is an integer greater than 1, the converter comprising;
N nonlinear amplifying means A1, . . . , AN, each having an output terminal supplying an output signal and input means operatively coupled to receive the output signals supplied by other amplifying means, one or more of the analog signal samples and a respective constant signal, the input means for taking the weighted sum of the signals received thereby, including applying respective weighting factors to the received signals, and providing the weighted sum to the amplifying means, wherein for any two of the N amplifying means Ai and Aj, where i and j are independent integers having values i=1, 2, . . . N and j=1, 2, . . . , N, the weighting factor Wij applied by the input means of Ai to the output signal supplied by Aj is the element of the ith row and jth column of a matrix -BT B, the weighting factor Kij applied by the input means of Ai to analog signal example uj is the element of the ith row and jth column of a matrix BT, the constant signal Ii received by the input means of Ai is the element of the ith row and ith column of the matrix -BT B, and the output signal supplied by Ai operatively stabilizes to binary value xi of the digital signal x. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
- N matrices, and N is an integer greater than 1, the converter comprising;
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11. A method for converting a discrete analog signal u, having N samples u1, . . . , uN each with a value between a first and a second level, into a digital signal x, having N corresponding 1-bit binary values x1, . . . , xN, such that a distortion measure d=(Au-Bx)T (Au-Bx) is minimized, where u and x are N-dimensional vectors, A and B are N×
- N matrices and N is an integer greater than 1, the method comprising the steps of;
providing N nonlinear amplifying means A1, . . . , AN, each receiving an input signal and supplying an output signal which is a sigmoid function of the input signal; and forming the input signal for each amplifying means by weighting the output signals supplied by other amplifying means and one or more of the analog signal samples by applying respective weighting factors thereto and summing the weighted output signals, the weighted analog signal sample and a respective constant signal, wherein for any two of the N amplifying means Ai and Aj, where i and j are independent integers having values i=1, 2, . . . , N and j=1, 2, . . . , N, the weighting factor Wij applied to the output signal supplied by Aj in forming the input signal for Ai is the element of the ith row and jth column of a matrix -BT B, the weighting factor Kij applied to the analog signal sample uj in forming the input signal for Ai is the element of the ith row and jth column of a matrix BT, the respective constant signal Ii of the input signal for Ai is the element of the ith row and ith column of the matrix -BT B, and the output signal supplied by Ai operatively stabilizes to binary value xi of the digital signal x. - View Dependent Claims (12, 13, 14, 15, 16)
- N matrices and N is an integer greater than 1, the method comprising the steps of;
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17. A nonstandard analog-to-digital converter for converting a discrete analog signal u having N samples u1, . . . , uN, into a digital signal x, having N corresponding m-bit binary values x1, . . . , xN, each equal to one of 2m predefined quantization levels, such that a distortion functions d=[A(u-Q)-B(x'"'"'-Q)]2 is minimized, where N and m are integers greater than 1, u and x'"'"' are N-dimensional vectors having values u1, . . . , uN and analog representations x'"'"'1, . . . , x'"'"'N of the binary values x1, . . . , xN, respectively, Q is an N-dimensional vector having first quantized values Q1, . . . , QN equal to quantization levels closest to and smaller than corresponding samples of u, and A and B are N×
- N matrices, the converter comprising;
truncating quantizer means operatively coupled to receive the analog signal samples u1 . . . , uN for providing the first quantized values Q1, . . . QN and binary representations Qb1, . . . QbN of the first quantized values; analog subtraction means operatively coupled to receive the analog signal samples u1, . . . , uN and the first quantized values Q1, . . . , QN for taking the difference between corresponding ones of the analog signal samples and the first quantized values to provide respective difference values u1, . . . , uN, where each difference value ui is equal to ui -Qi for i=1, 2, . . . , N; N nonlinear amplifying means A1, . . . , AN, each having an output terminal supplying an output signal and input means operatively coupled to receive the output signals supplied by other amplifying means, one or more of the difference values and a respective constant signal, the input means for taking the weighted sum of the signals received thereby, including applying respective weighting factors to the received signals and providing the weighted sum to the amplifying means, wherein for any two of the N amplifying means Ai and Aj, where i and j are independent integers having values i=1, 2, . . . , N and j=1, 2, . . . , N, the weighting factor Wij applied by the input means of Ai to the output signal supplied by Aj is the element of the ith row and jth column of a matrix -BT B, the weighting factor Kij applied by the inputs means of Ai to uj is the element of the ith row and jth column of a matrix BT, and the respective constant signal Ii received by the input means of Ai is the element of the ith row and ith column of the matrix -BT B; and digital adder means coupled to receive the output signals supplied by the N amplifying means and the binary representations Qb1, . . . , QbN of the first quantized values provided by the truncating quantizer means for summing the output signal supplied by each amplifying means Ai and the binary representation Qbi corresponding to analog signal sample ui to provide a binary value xi of the signal x. - View Dependent Claims (18, 19, 20, 21, 22, 23, 24, 25, 26)
- N matrices, the converter comprising;
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27. A method for converting a discrete analog signal u, having N samples u1, . . . , uN, into a digital signal x having N corresponding m-bit binary values x1, . . . , xN each equal to one of 2m predefined quantization levels, such that a distortion function d=[A(u-Q)-B(x'"'"'-Q)]T [A(u-Q)-B(x'"'"'-Q)] is minimized, where N and m are integers greater than 1, u and x'"'"' are N-dimensional vectors having values u1, . . . , UN and analog representations x1 '"'"', . . . xN '"'"' of the binary values x1, . . . , xN, respectively, Q is an N-dimensional vector having values Q1, . . . , QN equal to quantization levels closest to and smaller than corresponding values of u, and A and B are N×
- N matrices, the method comprising the steps of;
deriving N first quantized values Q1, . . . , QN corresponding to the N analog signal samples u1, . . . , uN, each of the first quantized values being the quantization level closest to and smaller than its corresponding analog signal sample; deriving N binary representations Qb1, . . . , QbN of the first quantized values Q1, . . . , QN ; subtracting each of the first quantized values from its corresponding analog signal sample to obtain a difference value corresponding to the analog signal sample, where each difference value ui is equal to ui -Qi for i=1, 2, . . . , N; providing N nonlinear amplifying means A1, . . . , AN, each receiving an input signal and providing an output signal which is a sigmoid function of the input signal; forming the input signal for each amplifying means by weighting the output signals supplied by other amplifying means and a respective one or more of the difference values by applying respective weighting factors thereto and summing the weighted output signals, the weighted difference values, and a respective constant signal, wherein for any two of the N amplifying means Ai and Aj, where i and j are independent integers having values i=1, 2, . . . , N and j=1, 2, . . . , N, the weighting factor Wij applied to the output signal supplied by Aj in forming the input signal for Ai is the element of the ith row and jth column of a matrix -BT B, the weighting factor Kij applied to the difference value uj in forming the input signal for Ai is the element of the ith row and jth column of a matrix BT, the respective constant signal Ii of the input signal for Ai is the element of the ith row and ith column of the matrix -BT B; and summing the output signal supplied by each amplifying means Ai and binary representation Qbi corresponding to analog signal sample Ui to obtain a corresponding binary value xi of the digital signal x. - View Dependent Claims (28, 29, 30, 31, 32)
- N matrices, the method comprising the steps of;
Specification