Howtosignalprocessing
- What is wavelet neural network?
- What is adaptive wavelet?
- What is a neural network model?
- What are neural networks used for?
What is wavelet neural network?
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 success in a wide range of applications. However a general accepted framework for applying WNs is missing from the literature.
What is adaptive wavelet?
Adaptive wavelet transform (AWT) is then defined as an average of short-time CWT (STCWT) segments that are staggered over time. Two algorithms are proposed to determine the optimal time-varying wavelet parameters from an arbitrary dynamic response with no prior knowledge.
What is a neural network model?
A neural network is a simplified model of the way the human brain processes information. It works by simulating a large number of interconnected processing units that resemble abstract versions of neurons. The processing units are arranged in layers.
What are neural networks used for?
Why are neural networks important? Neural networks can help computers make intelligent decisions with limited human assistance. This is because they can learn and model the relationships between input and output data that are nonlinear and complex.
