In particular, we cannot simply gather the function codes at regular time intervals as function control samples to train the behavior model, and the intrinsic reasons include the following: (1) the number of function codes at each regular time interval is distinct, and the prerequisite for the behavior model based on
WNN is that the dimensions of input samples must be consistent with one another; (2) the number of function codes at each regular time interval may be very large, and it may waste computational resources and reduce detection efficiency.
In the quantitative prediction aspect, we use
WNN for time-series prediction.
The final desired trajectory of hip, knee, and ankle joint angles is generalized by the TS-FIS and
WNN architecture, on the basis of predefined membership functions:
Then, all IMF components and residuals are trained and predicted by
WNN method.
The
WNN consists of an input vectors, layer of weighted wavelets, and output vector.
Recently, a variety of wavelet neural networks (
WNN) have been proposed by combining the localization ability of wavelet transformation to reveal the properties of function with the learning ability and general approximation properties of neural networks.
AM 1470
WNN The Health and Wealth Network is a part of the Beasley Broadcast Network, and broadcasts throughout Broward and Palm Beach County.
Priya, "Combined wavelet transforms and neural network (
WNN) based fault detection and classification in transmission lines," in Proceedings of the International Conference on Control, Automation, Communication and Energy Conservation (INCACEC '09), pp.
Li, "Research on
WNN modeling based on an improved artificial Bee Colony algorithm for gold price prediction," Computational Intelligence and Neuroscience, vol.
However, in a recent article Poungponsri and Yu [51] come with an improvement of the method in [89] and the algorithm is tested also on PLI cancellation (Wavelet Neural Network--
WNN).
Wavelet neural network (
WNN), which was proposed in late 20th centuries, is a kind of local response type neural network and attracts many research interests in areas of intelligent computation.