scholar.google.com › citations
In this paper we present algorithms which are adaptive and based on neural networks and wavelet series to build wavenets function approximators.
In this paper we present algorithms which are adaptive and based on neural networks and wavelet series to build wavenets function approximators.
In this paper we present algorithms which are adaptive and based on neural networks and wavelet series to build wavenets function approximators.
Algorithms which are adaptive and based on neural networks and wavelet series to build wavenets function approximators to reduce convergence time to a ...
This study investigated the use of Wavelet Neural Networks (WNN) for signal approx- imation. The particular wavelet function used in this analysis consisted ...
Wavelets are a class of functions used to localise a given function in both position and scaling. They are used in applications such as signal processing and ...
Dive into the research topics of 'Wavelet neural network algorithms with applications in approximation signals'. Together they form a unique fingerprint. Sort ...
In this study, we present a complete statistical model identification framework in order to apply WNs in various applications. The following subjects were ...
People also ask
What is a wavelet in neural network?
How to train a neural network?
What are the benefits of neural networks?
How do neural networks work?
Abstract— Wavelet networks (WNs) are a new class of networks which have been used with great success in a wide range of application.
Wavelet networks are a new class of networks that combine the classic sigmoid neural networks (NNs) and the wavelet analysis (WA). WNs have been used with great ...