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rbf neuron circuit and its working method

A neuron and circuit technology, applied in biological neural network models, physical realization, etc., can solve the problems that RBF neural network software implementation is difficult to meet high-speed, portable, embeddable, etc.

Active Publication Date: 2018-12-25
FUZHOU UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Therefore, the software implementation of the RBF neural network is difficult to meet its high-speed, portable, and embeddable requirements in the field of artificial intelligence applications.

Method used

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  • rbf neuron circuit and its working method
  • rbf neuron circuit and its working method

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Embodiment Construction

[0024] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0025] The invention proposes an analog circuit implementation scheme of RBF neurons, which can generate a two-dimensional Gaussian-like function with a variable center and a variable shape by giving an appropriate external bias voltage. The RBF neuron circuit module is the most important basic unit in the RBF neural network circuit system, and can be used to build neural network circuits such as pattern classifiers and function approximators. The present invention can be integrated into a special neural network chip, which is small in size, easy to carry, and easy to embed into other systems. In addition, it can also achieve a high degree of parallel computing, which overcomes the shortcomings of software implementation of RBF neuron circuit modules, such as large volume, not easy to carry, not easy to embed, and slow computing speed.

[0026...

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Abstract

The present invention provides a RBF neurons circuit and its working method, which includes the first Gilbert multiplier, the second Gilbert multiplication, the square root circuit, the resistance and the Gaussian function to generate the circuit;The current output terminal of the multiplier is connected to the input terminal of the square root circuit respectively; the output end of the square root circuit connects one end of the resistor and the Gaussian function generates the current input terminal of the circuit; the other end of the resistor is grounded.By given the appropriate external bias voltage, a variable and variable two -dimensional Gaussian function can be generated.The present invention can be a special neural network chip, which has the advantages of small volume, portable, embedded, and other advantages. It can achieve high parallel computing, overcoming the software to achieve the large volume, difficulty carrying, not easy to embed, calculated by the RBF neuron circuit moduleSlow flaws.

Description

technical field [0001] The invention relates to a neuron circuit and its working method, in particular to an RBF neuron circuit and its working method. Background technique [0002] The theoretical model of RBF (Radial Basic Function) neural network has been widely used in artificial intelligence fields such as pattern classification and function approximation, but it is still mainly focused on the traditional computer software simulation implementation. The software implementation of RBF neural network uses a general-purpose CPU processor, which is inconvenient to embed into other application systems, and relies on a huge general-purpose computer system to complete learning calculations, which is not portable. During the calculation process, the CPU often waits until the neurons of the RBF are calculated one by one before calculating the total result. The serial calculation method is adopted, and the speed is relatively slow. Therefore, the software implementation of RBF n...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06N3/06
CPCG06N3/065
Inventor 魏榕山姚诗晖刘恋陈林城
Owner FUZHOU UNIV
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