基于小波神经网络的双足步行机器人步态规划控制器(英文)

Gait planning controller of biped robot using wavelet neural networks

对于传统的神经网络中神经元模型在结构和信息存储能力上存在的不足 ,本文提出了一种基于广义小波基函数网络的神经元集聚模型。这种小波神经网络不仅收敛速度快 ,非线性逼近能力更好 ,而且具有内部结构变尺度、自适应调整和广义信息存储等智能化特点 ,更符合生物原型的实际情况。静态学习和准动态学习仿真实验证明这种神经网络结构的有效性。

Considering the deficiency in the structure as well as in the capability of information storage of the neuron models used in traditional neuron networks,an intelligent neuron assemblage model with generalized wavelet basis function network as its stimulating function is proposed.The wavelet neural network not only converges much faster with better nonlinear approaching capability,but also is characterized by its ability in variable scale adaptive structure adjustment and the generalized information storage,etc,which guarantee the network reflects the biological prototype much more faithfully.Static and pseudo dynamic learning is demonstrated to prove the validity of the proposed mechanism.