A self-generated neural network construction method

A construction method and neural network technology, applied in the field of self-generating neural network construction to reduce the influence of human subjective factors

Active Publication Date: 2017-12-19
XIAMEN IND TECH RES INST CO LTD
View PDF2 Cites 1 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] In order to overcome the shortcomings of the above-mentioned prior art, the object of the present invention is to provide a method for constructing a self-generated neural network, which maps the characteristics of the biological neural model and the appropriate heuristic algorithm to the silicon-based circuit, so that the neural network can pass the model Self-generating and self-organizing, avoiding the shortcomings of artificial neural networks

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • A self-generated neural network construction method
  • A self-generated neural network construction method
  • A self-generated neural network construction method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0034] The implementation of the present invention will be described in detail below in conjunction with the drawings and examples.

[0035] The biological neural network has gone through a long evolutionary process to form an extremely complex and large-scale neural network system. Biologists have been researching biological neural networks for hundreds of years, but so far they still know little about the working principles of biological neural networks. Not to mention the understanding of the neural network principles of brain nerves, which have cognition, learning, and innovation methods. Facing such complex neural networks, research methods need to be adjusted. It is not possible to continue to follow the research ideas of artificial neural networks, but to study self-organizing and self-growing silicon-based neural networks from the perspective of bionics. What needs to be clearly stated here is not to try to copy a silicon-based neural network that is the same as or s...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

A method for constructing a self-generated neural network, comprising the following steps: Step 1, adding a stimulus signal; Step 2, evaluating the neuron output strength, determining the connection direction of the neuron, continuously forming network connections, and finally generating an initial network; Step 3, Calculate the position and probability of connecting to the target neuron; step 4, judge whether the current network generation process is stopped, if so, then go to step 5, otherwise go to step 2 to continue; step 5, optimize the network connection through the optimization algorithm; Step 6, judge whether it is necessary to add stimulation, if not, then end, otherwise go to step 1; the network proposed by the present invention is a self-generated network, which can effectively reduce the influence of human subjective factors. Based on neural theory, it is possible to further explore the neural brain and realize real intelligence.

Description

technical field [0001] The invention belongs to the technical field of neural network calculation, relates to a software-oriented modeling method and a hardware-realized neural network self-generation method, in particular to a self-generated neural network construction method. Background technique [0002] With the development of computers today, both computing power and power consumption have been substantially improved in performance. But with the diversification of people's needs, the current computer structure exposes more and more problems. There are two types of information processing problems provided by nature: structured and unstructured. A structural problem means that it can be clearly and strictly described in mathematical language, and the realization algorithm of the problem can be formulated and mapped to a computer program, and then processed by computer instructions. Traditional von Neumann machines far outperform humans in solving such problems. Non-str...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Patents(China)
IPC IPC(8): G06N3/04G06N3/063G06N3/08
CPCG06N3/04G06N3/08G06N3/065
Inventor 何虎许志恒马海林王玉哲王旭
Owner XIAMEN IND TECH RES INST CO LTD
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products