Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Neuromorphic system based on variable-resistance devices and adaptive-excited neurons and realization method

A technology of resistive switching devices and morphological systems, applied in neural learning methods, physical realization, biological neural network models, etc., can solve problems that limit the development and application of neuromorphic systems, independent training, unsupervised learning, etc., and achieve more accurate regulation Flexibility, area reduction effect

Active Publication Date: 2017-10-20
PEKING UNIV
View PDF4 Cites 18 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Due to the challenging design of peripheral circuits, existing systems cannot be independently trained without a computer, or can only perform unsupervised learning, which severely limits the development and application of neuromorphic systems.

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
  • Neuromorphic system based on variable-resistance devices and adaptive-excited neurons and realization method
  • Neuromorphic system based on variable-resistance devices and adaptive-excited neurons and realization method
  • Neuromorphic system based on variable-resistance devices and adaptive-excited neurons and realization method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0030] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided for more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0031] like figure 1 As shown, the trainable neuromorphic system based on resistive switching devices involved in the present invention mainly includes the following parts: 1, cross array of resistive switching devices; 2, front neurons; 3, rear neurons; 4, global dynamic threshold control circuit ;5. Control logic module; 6. Voltage regulation module; 7. Sample input; 8. Label input; 9. Result output.

[0032] Among them, sample...

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

The invention discloses a neuromorphic system based on variable-resistance devices and adaptive-excited neurons and a realization method. The system includes a crossed array of the variable-resistance devices, the anterior neurons, the posterior neurons, a global dynamic threshold value control circuit, a control logic module, a voltage regulation module, a sample input, a tag input and a result output. According to the system, the variable-resistance devices are used as electronic synapses, and a new structure and operation mode of the adaptive-excited neurons are provided, thus the system is optimized on area and operation aspects, and training problems faced by the same type of systems are solved.

Description

technical field [0001] The invention adopts a novel resistive variable device to design a trainable neuromorphic system, is a parallel hardware implementation of an artificial neural network, and belongs to the technical field of integrated circuits, artificial intelligence and neural network systems. Background technique [0002] Neural networks are one of the most widely used and accomplished techniques in the field of artificial intelligence. The current neural network algorithm implementation includes two aspects: software implementation and hardware implementation. Among them, there is a Von Neumann bottleneck in the modern computer on which the software implementation depends, that is, in the Von Neumann structure, the computing module and the storage unit are separated, and the CPU must first read data from the storage unit when executing commands, and the central Frequent data transmission between the processor and the memory needs to pass through the bus, and the l...

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 Applications(China)
IPC IPC(8): G06N3/06G06N3/08
Inventor 康晋锋江宇宁黄鹏周正柳晨韩润泽刘晓彦刘力锋
Owner PEKING UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com