Continuous Wavelet Transform and Discrete Wavelet Transform

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Resource Overview

This is a final project on wavelet application engineering programs, which includes implementations of both Continuous Wavelet Transform (CWT) and Discrete Wavelet Transform (DWT), designed specifically for beginners to understand and apply wavelet analysis techniques.

Detailed Documentation

This final project focuses on wavelet application engineering programs, implementing both Continuous Wavelet Transform (CWT) and Discrete Wavelet Transform (DWT). The Continuous Wavelet Transform is a mathematical tool that decomposes signals into different frequency components using wavelet scaling and shifting operations, typically implemented through convolution operations with various wavelet basis functions. The Discrete Wavelet Transform serves as the discretized version of CWT, commonly applied in signal compression, noise removal, and pattern recognition through multi-resolution analysis algorithms like Mallat's pyramid algorithm. This project is particularly suitable for beginners, providing practical code examples that help users understand fundamental wavelet transform concepts and principles, including wavelet filter bank implementations and signal decomposition/reconstruction techniques.

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