Abstract
We found that neuron model is inadequate owing to its defects such as those inherent in its structure and in its capability of information storage. So we propose an intelligent neurons assemblage model with generalized wavelet basis function network as its excited function. Not only the wavelet neural networks’ convergence rate is much faster and its nonlinear approach capability is much better but also its intelligent characteristics, such as the variable-scale adaptive adjustment of structure and the generalized information storage, make it reflect much more faith fully the biological original. Static learning of the inverse dynamics model and adaptive virtual torque control based on Lyapunov stability of the carrying robot walking are demonstrated to prove that the proposed mechanism is valid.
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Yang, X., Zhang, Y., Xia, C., Yang, Z., Gu, W. (2008). An Application of Wavelet Networks in the Carrying Robot Walking. In: Sun, F., Zhang, J., Tan, Y., Cao, J., Yu, W. (eds) Advances in Neural Networks - ISNN 2008. ISNN 2008. Lecture Notes in Computer Science, vol 5264. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87734-9_22
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DOI: https://doi.org/10.1007/978-3-540-87734-9_22
Publisher Name: Springer, Berlin, Heidelberg
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