Adaptive Wavelet Techniques for Pattren Analysis

Wavelet analysis, a computational method, decomposes data into frequency components, analyzed by scale, effective for signals with discontinuities. Originating from diverse fields like mathematics, physics, and engineering, wavelet theory finds applications in image compression, radar, and more. Using scalable wavelet functions, it allows precise signal reconstruction, differing from constant scale methods. This study compares adapted and traditional wavelets, emphasizing Finite Impulse Response (FIR) efficiency. Applying these wavelets for pattern recognition, particularly in spike detection in EEG data, highlights their versatility in complex signal processing.