Name
Abstract | ||
|---|---|---|
Modern subspace-based algorithms can offer high-resolution spectral estimates but with a cost of high computational complexity for the eigenvalue decomposition (EVD) involved. We propose a novel preprocessing scheme which can be used in conjunction with the subspace-based algorithms to alleviate the high computations previously required. The new scheme is to demodulate the input data first, and then takes the computationally efficient discrete-time Haar wavelet transform (HWT). Only the principle subband component (PSC) of the transformed data is kept for further processing, which not only retains the same amount of information but also possesses the same characteristic as that of the original (noiseless) harmonic data. The subspace-based algorithms are thus applicable to this new set of transformed data but with substantially reduced computational load. Some simulation results are provided to justify the proposed approach |
Year | DOI | Venue |
|---|---|---|
1997 | 10.1109/ICASSP.1997.599269 | ICASSP |
Keywords | Field | DocType |
preprocessing scheme,demodulation,simulation results,signal processing,input data demodulation,discrete time haar wavelet transform,wavelet transforms,parameter estimation,noiseless harmonic data,harmonic retrieval problem,transformed data,subspace based algorithms,computational complexity,high computational complexity,efficient haar wavelet-based approach,harmonic analysis,computational load reduction,eigenvalue decomposition,transforms,eigenvalues and eigenfunctions,high resolution spectral estimates,principle subband component,spectral estimation,frequency,high resolution,multiple signal classification,marine technology,discrete time | Signal processing,Mathematical optimization,Subspace topology,Pattern recognition,Computer science,Harmonic analysis,Preprocessor,Artificial intelligence,Eigendecomposition of a matrix,Haar wavelet,Wavelet transform,Computational complexity theory | Conference |
Volume | ISSN | ISBN |
3 | 1520-6149 | 0-8186-7919-0 |
Citations | PageRank | References |
1 | 0.39 | 3 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Y. Chu | 1 | 1 | 0.39 |
| W.-H. Fang | 2 | 14 | 4.65 |
| S.-H. Chang | 3 | 1 | 0.39 |