Matching Pursuit Algorithm
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This text discusses the Matching Pursuit algorithm, which employs linear combinations to represent Gabor atom sets, thereby reducing computational complexity. Specifically, Matching Pursuit is a signal processing technique that decomposes signals into a set of atoms whose linear combinations effectively approximate the original signal. In implementation, the algorithm iteratively selects the atom from a predefined dictionary that best matches the signal residual, subtracting its contribution at each step. Key computational optimizations include using inner product calculations to identify optimal atom matches and orthogonal projections for residual updates. Widely applied in signal and image processing, this method significantly reduces computational demands while accelerating processing speed. Thus, Matching Pursuit serves as a valuable tool for efficient signal data analysis and processing.
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