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Nonlinear self-feedback chaotic neural network signal blind detection method

A neural network and self-feedback technology, applied in the field of nonlinear self-feedback chaotic neural network signal blind detection, can solve the problem of slow energy function convergence speed and other problems

Inactive Publication Date: 2016-11-16
NANJING UNIV OF POSTS & TELECOMM
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Problems solved by technology

However, TCNN has negative self-coupling, which will lead to slower convergence of the energy function

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  • Nonlinear self-feedback chaotic neural network signal blind detection method
  • Nonlinear self-feedback chaotic neural network signal blind detection method
  • Nonlinear self-feedback chaotic neural network signal blind detection method

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[0057] Below in conjunction with accompanying drawing, the signal blind detection method based on double Sigmoid nonlinear self-feedback chaotic neural network that the present invention proposes is described in detail:

[0058] The blind signal detection method based on double Sigmoid nonlinear self-feedback chaotic neural network, its implementation process is as follows:

[0059] When ignoring noise, the receiver equation for a discrete-time channel is defined as

[0060] x N =SΓ T (1)

[0061] In the formula, X N is the receiving data array, S is the sending signal array, Γ is the channel impulse response h jj Constituted block Toeplitz matrix; ( ) T Represents matrix transposition;

[0062] Among them, the sending signal array:

[0063] S=[s L+M (k),...,s L+M (k+N-1)] T =[s N (k),...,s N (k-M-L)] N×(L+M+1) ,

[0064] M is the channel order, L is the equalizer order, and N is the required data length;

[0065] the s L+M (k)=[s(k),...,s(k-L-M)] T ; Among t...

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Abstract

The present invention proposes a nonlinear self-feedback chaotic neural network signal blind detection method, which uses a nonlinear function as the self-feedback item of the chaotic neural network, and applies the double Sigmoid function to the blind detection method. In each iteration, it first enters the chaos neural network, and then into the second activation function. Because the chaotic neural network has the advantage of being able to avoid being trapped in a local optimum, the present invention inherits this characteristic of the chaotic neural network and improves blind detection performance; and, compared with the chaotic neural network of the linear self-feedback item, the non-linear self-feedback The chaotic neural network has more complex dynamic behavior, which makes the internal state of the network have more efficient chaotic search ability and search efficiency. Under the same conditions, the method of the invention has better anti-noise performance than the traditional Hopfield signal blind detection method.

Description

technical field [0001] The invention belongs to the technical field of wireless communication signal processing and neural network, in particular to a nonlinear self-feedback chaotic neural network signal blind detection method. Background technique [0002] The rapid development of data communication and wireless sensor network technology has put forward higher requirements for the blind detection of communication signals (BlindDetection). The so-called blind detection can detect the transmitted signal only by using the received signal itself, thereby eliminating inter-symbol interference (ISI) to improve the information transmission rate and reliability. [0003] In order to solve the low utilization rate of channel bandwidth easily caused by traditional adaptive equalization technology, many literatures began to use Hopfield neural network to study the problem of blind signal detection. The Hopfield Neural Network (Hopfield Neural Networks, HNN) blind detection algorithm...

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Application Information

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IPC IPC(8): H04L1/00H04L25/03H04L27/00
CPCH04L1/0038H04L25/03165H04L27/001
Inventor 张昀梅可季奎明于舒娟徐荣青杨恒新屈科谢娜
Owner NANJING UNIV OF POSTS & TELECOMM
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