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Wavelet neural network processor based on SOPC (System On a Programmable Chip)

A technology of wavelet neural network and processor, which is applied in biological neural network models, shaping networks in transmitters/receivers, physical realization, etc., can solve the problems of size and power consumption limiting the development and application of wavelet neural networks, and achieve Effects of shortening the design cycle and increasing the operating speed

Inactive Publication Date: 2010-11-10
CHANGAN UNIV
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AI Technical Summary

Problems solved by technology

Due to its cost, size and power consumption, the further development and application of wavelet neural network are also limited.

Method used

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  • Wavelet neural network processor based on SOPC (System On a Programmable Chip)
  • Wavelet neural network processor based on SOPC (System On a Programmable Chip)
  • Wavelet neural network processor based on SOPC (System On a Programmable Chip)

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Experimental program
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Embodiment Construction

[0030] Such as figure 1 , figure 2 As shown, a wavelet neural network processor based on sopc is composed of forward propagation module 1, error feedback module 2 and network update module 3. The output of the forward propagation module 1 is connected to the error feedback module 2 , the output of the error feedback module 2 is connected to the network update module 3 , and the output of the network update module 3 is connected to the forward propagation module 1 .

[0031] The forward propagation module 1 includes a forward propagation input layer functional module 1-1, a forward propagation hidden layer functional module 1-2, and a forward propagation output layer functional module 1-3.

[0032] The forward propagation input layer function module 1-1 is composed of several data registers.

[0033] The forward propagation hidden layer function module 1-2 is composed of several forward propagation hidden layer reconfigurable units RC1-1 and the same number of wavelet functi...

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Abstract

The invention relates to a wavelet neural network processor based on an SOPC (System On a Programmable Chip), comprising a forward transmission module, an error feedback module and a network updating module, wherein the output end of the forward transmission module is connected to the error feedback module; the output end of the error feedback module is connected to the network updating module; the output end of the network updating module is connected to the forward transmission module; the forward transmission module comprises a forward transmission input layer function module, a forward transmission hidden layer function module and a forward transmission output layer function module; the error feedback module comprises an error feedback output layer function module and an error feedback hidden layer function module; and the network updating module comprises a network updating output layer function module and a network updating hidden layer function module. In the invention, a wavelet neural network is realized on the SOPC, and a wavelet neural network arithmetic is divided into several basic operations; the basic operations are completed by a reconfigurable cell (RC), and the wavelet neural network with different functions can be formed by adopting different RC connection modes.

Description

technical field [0001] The invention relates to a wavelet neural network processor, in particular to a wavelet neural network processor based on SOPC. Background technique [0002] Wavelet Neural Network (WNN) is the product of the combination of wavelet analysis theory and neural network theory. Pati and Krishaprasad proposed the discrete affine wavelet network model. The basic idea is to introduce the discrete wavelet transform into the neural network model, and then construct the wavelet neural network through the affine frame in the translation and expansion of the Sigmoid function. Zhang Qinghua et al. formally proposed the concept of wavelet neural network in 1992. The idea is to replace neurons with wavelet elements, that is, replace the Sigmoid function with the positioned wavelet function as the activation function, and establish the relationship between wavelet transformation and network coefficients through affine transformation. Connection. [0003] In the spec...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/063H04L25/03
Inventor 文常保巨永锋闫栋康迤任东明刘清洪李洪安
Owner CHANGAN UNIV
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