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中文摘要：
针对粒子群算法具有不易陷入局部极小、收敛速度快等特点，提出了一种基于粒子群的小波神经网络学习算法，优化了小波神经网络中的各个参数，并将该方法应用于函数仿真试验。试验表明，该算法能减少迭代次数、提高收敛精度，是小波网络的有效训练算法。
英文摘要：
A wavelet neural networks（WNN） learning algorithm based on particle swarm optimization （PSO） is proposed to optimize parameters of WNN in this paper, as this new algorithm has some virtues such as high convergence speed and not easily trapping local minima. Then, the algorithm is applied to neural network＇s training in simulating function. The experimental result indicates that this algorithm can reduce the number of training and error, and is an effective training algorithm to WNN.
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