Device and method for executing artificial neural network self-learning operation

An artificial neural network and self-learning technology, which is applied in the field of devices that perform artificial neural network self-learning operations, can solve the problems of high front-end decoding power consumption, low performance of general-purpose processors, and high data access overhead of general-purpose processors, etc. problem, to achieve the effect of streamlining the front-end decoding overhead

Active Publication Date: 2017-11-03
CAMBRICON TECH CO LTD
View PDF5 Cites 90 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] What the present invention is to solve is that in the prior art, general-purpose processors (GPU, CPU) need a series of simple operations and memory access operations for pre-training of multi-layer neural networks, and the po...

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
  • Device and method for executing artificial neural network self-learning operation
  • Device and method for executing artificial neural network self-learning operation
  • Device and method for executing artificial neural network self-learning operation

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0033] Other aspects, advantages and salient features of the present invention will become apparent to those skilled in the art from the following detailed description of exemplary embodiments of the present invention when taken in conjunction with the accompanying drawings.

[0034] In the present invention, the terms "include" and "comprising" and their derivatives mean to include but not limit; the term "or" is inclusive, meaning and / or.

[0035]In this specification, the various embodiments described below to describe the principles of the present invention are illustrative only and should not be construed as limiting the scope of the invention in any way. The following description with reference to the accompanying drawings is provided to assist in a comprehensive understanding of exemplary embodiments of the present invention as defined by the claims and their equivalents. The following description includes numerous specific details to aid in understanding, but these sho...

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 device and method for executing artificial neural network self-learning operation. The device comprises an instruction storage unit, a controller unit, a data access unit, an interconnection module, a primary operation module and a plurality of secondary operation modules. According to the device and method, the self-learning pre-training of a multilayer neural network can adopt a layer-by-layer training manner; for each layer of network, the self-learning pre-training is completed after multiple operations are iterated until the weight is updated to be smaller than a certain threshold value. Each iteration process can be divided into four stages, calculation is carried out in the first three stages to respectively generate a first-order hidden layer median, a first-order visible layer median and a second-order hidden layer median, and the weight is updated in the last stage by utilizing the medians in the first three stages.

Description

technical field [0001] The invention relates to artificial neural network technology, in particular to a device and method for performing artificial neural network self-learning operations. Background technique [0002] Multi-layer artificial neural networks are widely used in the fields of pattern recognition, image processing, function approximation, and optimization calculations. In recent years, multi-layer artificial networks have been favored by academic circles and researchers due to their high recognition accuracy and good parallelism. industry is getting more and more attention. [0003] A typical multi-layer artificial neural network training method is the backpropagation (BP) algorithm. This method is a representative type of supervised learning, which requires a large number of labeled training samples during the training process, but the cost of sample collection is very high. At the same time, during the training process of this method, the error correction s...

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
IPC IPC(8): G06N3/063G06N3/08
CPCG06N3/063G06N3/08G06N3/045
Inventor 李震郭崎陈云霁陈天石
Owner CAMBRICON TECH 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

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap