A frequency hopping sequence prediction method based on optimized wavelet neural network

A technology of wavelet neural network and frequency hopping sequence, which is applied to biological neural network models, neural architectures, data exchange networks, etc., can solve the problem of not being able to adaptively determine the initial value of the wavelet translation factor for the number of hidden layer nodes, no universal and effective Algorithms and other issues to achieve the effect of speeding up the learning speed and prediction speed, shortening the running time, and reducing the complexity

Active Publication Date: 2018-12-21
UNIV OF SCI & TECH BEIJING
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Problems solved by technology

[0004] The object of the present invention is: the present invention provides a kind of frequency hopping sequence prediction method based on optimized wavelet neural network, solves when using wavelet neural network to predict different frequency hopping sequence

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  • A frequency hopping sequence prediction method based on optimized wavelet neural network
  • A frequency hopping sequence prediction method based on optimized wavelet neural network
  • A frequency hopping sequence prediction method based on optimized wavelet neural network

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Embodiment 1

[0098] In step 1, the time domain analysis adopts the combined spectrogram method:

[0099] Step 1.1: Sampling the received frequency hopping signal to obtain a sequence x(n) of length N, find the corresponding analytical signal Z(n), and perform time-frequency analysis of Z(n) by combined spectrogram method; combined spectrogram The same signal is analyzed twice with wide window function and narrow window function respectively, and two sets of results with high frequency resolution and high time resolution are obtained respectively, and then the two results are combined to obtain Time-frequency analysis results with good time-frequency focus.

[0100] Step 1.2: After the signal is processed by the combined spectrogram method, its energy distribution is concentrated at the instantaneous frequency. Therefore, in each frequency hopping period, the frequency corresponding to the maximum value of the signal energy amplitude is the frequency hopping frequency in this period; using...

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Abstract

The invention discloses a frequency hopping sequence prediction method based on an optimized wavelet neural network, belonging to the frequency hopping sequence prediction method field. 1, performingtime domain analysis on frequency hopping signal to obtain the frequency hopping sequence at the current time; 2, preprocessing frequency hopping sequence to obtain a training sample and a test sample; 3, inputting training sample into the initialized neural network to carry out DBSCAN clustering calculation and weight optimization sequentially to complete the training; 4, inputting test sample into a trained neural network for prediction, and obtaining a frequency hopping sequence at the next time; The invention solves the problem that when the wavelet neural network is used for predicting different frequency hopping sequences, there is no universal and effective algorithm in the network training process, which leads to the problem that the number of hidden layer nodes and the initial value of wavelet translation factor can not be determined adaptively. The prediction accuracy of the same hidden layer node network is improved, the subsequent learning speed of the network is accelerated, and the running time of the program is shortened.

Description

technical field [0001] The invention belongs to the field of frequency hopping sequence prediction methods, in particular to a frequency hopping sequence prediction method based on an optimized wavelet neural network. Background technique [0002] Frequency hopping communication belongs to a method of spread spectrum communication. It is a "multi-frequency, code selection, and frequency shift keying" system. It has the characteristics of flexibility, large multi-access capacity, high frequency band utilization and strong anti-interference ability. It is widely used in military communication and civilian mobile communication. The research on the prediction of frequency hopping sequences can not only realize the alignment interference of frequency hopping signals, reduce the cost of power consumption, but also play a vital role in improving the blind reception performance of frequency hopping signals; therefore, the estimation of frequency hopping sequences The research on th...

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Application Information

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IPC IPC(8): H04B1/713G06N3/04H04L12/24
CPCH04B1/713H04L41/147G06N3/045
Inventor 陈媛张竞文阳小龙孙奇福
Owner UNIV OF SCI & TECH BEIJING
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