Controlled selection of inputs

• US 20040111385A1
• Filed: 01/13/2004
• Published: 06/10/2004
• Est. Priority Date: 01/15/2001
• Status: Abandoned Application

• Current Assignee: Aberdeen University
• Original Assignee: Aberdeen University
• Inventors: Starkey, Andrew Joe
• Application Number:
  US10/466,401
• Publication Number:
  US 20040111385A1
• Time in Patent Office: Days
• US Class Current: 706/46
• CPC Class Codes: G06N 3/08 Learning methods

Abstract

The invention relates to a selection process for input parameters intended for application to an intelligent processing system such as a neural network, or in the implementation of an intensive data handling operation, such as data mining. The selection process involves producing an indication of the state of organisation of the parameters and selecting them for use in the processing system or data handling operation if their state of organisation is indicated to be sufficient. If the state of organisation of the parameters is not deemed sufficient, their various influences are automatically determined and at least one parameter tending to disturb the state of organisation is rejected. A revised indication of the state of organisation of the remaining parameters is then produced, and the selection process is repeated until either a satisfactory indication is produced, at which point the relevant parameters are applied to the processing system or data handling operation, or insufficient parameters remain to produce a reliable indication.

Claims

1. A process for selecting input parameters for application to an intelligent processing system or a data manipulating operation, the process including the steps of:

—

(a) applying said input parameters to a pre-processor capable of providing an indication of a state of organisation of said parameters as a whole,

(b) selecting said parameters if the state of said organisation of said parameters as a whole is determined to be sufficient;

otherwise;

(c) analysing said indication to determine the influence of at least some of said input parameters thereupon,

(d) rejecting one or more of said parameters based upon the degree of said influence, and

(e) repeating steps (a), (b), (c) and (d) until the said state of organisation of said parameters as a whole is determined to be sufficient.

2. A process according to claim 1 intended to subject input parameters to automatic and iterative pre-processing in order to ensure that those parameters selected make a positive contribution to said system or operation.

3. A process according to claim 1 or claim 2 wherein the intelligent processing system comprises a neural network.

4. A process according to claim 3 wherein said neural network is selected for general applicability to the nature of the information to be processed thereby, and self-trained in operation, by repeated exposure to the relevant input parameters, to render it usefully responsive to the specifics of a system or process to which the parameters relate.

5. A process according to any preceding claim wherein the said steps of analysing said indication to determine the influence of at least some of said input parameters thereupon, and rejecting ne or more of said parameters based upon the degree of said influence take account both of positive and negative influences of said parameters on the said state of organisation of said parameters as a whole, thereby to permit rejection of parameters that have a tendency to disorganise other information as well as those which are of no direct assistance in organising such information.

6. A process according to any preceding claim wherein input parameters are selected in dependence upon their tendency to relate to common recognisable information conditions and/or their tendency not to suppress other relevant information.

7. A process according to any preceding claim further comprising the steps of storing the results of previous input data sets and, if a current performance of the pre-processor is worse than that at a previous step, causing the process to revert to the input data set of said previous step.

8. A process according to any preceding claim wherein the input parameters are derived from data samples and the pre-processor is adapted to select data samples in correlated groups;

each group conforming to a respective condition distinct from that of other groups.

9. A process according to any preceding claim, wherein the pre-processor is constituted by a self-organising map (SOM) processor capable of providing an indication of a state of organisation of input parameters applied thereto, and thus of the influence that such parameters will have upon the performance of the intelligent processing system or the manipulating operation to which they are applied.

10. A process according to claim 9 wherein the SOM is used iteratively to effect retention or rejection, as appropriate, of various input parameters.

11. A process for selecting input parameters for application to an intelligent processing system or a data manipulating operation;

the process being in substantial conformance with any generic or detailed configuration thereof herein described.