Fast Computation of Tower Spectral Kurtosis Map for 1D Signals
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To efficiently compute the tower spectral kurtosis map for 1D signals, we can identify the interval where spectral kurtosis reaches its maximum value, which simplifies the determination of required filter parameters including center frequency and bandwidth. This approach enables more accurate signal analysis and subsequent filtering operations. During computation, we can employ optimized algorithms such as Fast Fourier Transform (FFT)-based spectral estimation and sliding window techniques to improve computational efficiency and accuracy. Key implementation steps include calculating spectral kurtosis across multiple frequency bands using overlap-add processing and applying peak detection algorithms to locate maximum kurtosis regions. This methodology provides deeper insights into signal spectral characteristics and supports targeted processing optimizations through adaptive filtering based on identified frequency intervals.
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