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حوزهپردازش سیگنالپردازش سیگنال
خانوادهProcess / pipelineProcess / pipeline
سال پیدایش19671949
پدیدآورPeter WelchNorbert Wiener
نوعFrequency domain signal analysisLinear mean-square optimal filter
منبع بنیادینWelch, P. (1967). The Use of Fast Fourier Transform for Estimation of Power Spectra: A Method Based on Time Averaging over Short, Modified Periodograms. IEEE Transactions on Audio and Electroacoustics, 15(2), 70–73. DOI ↗Wiener, N. (1949). Extrapolation, Interpolation, and Smoothing of Stationary Time Series. John Wiley & Sons. link ↗
نام‌های دیگرPSD Estimation, Spectral Density Analysis, Power Spectrum EstimationWiener Optimal Filter, Kolmogorov-Wiener Filter, Mean-Square Optimal Filter
مرتبط44
خلاصهPower Spectral Density (PSD) estimation is a set of methods for determining how the power of a signal is distributed across different frequencies. Proposed by Peter Welch in 1967, PSD estimation techniques are fundamental to frequency domain signal analysis, providing insights into the frequency composition of signals for applications ranging from communications to biomedical monitoring.The Wiener filter is an optimal linear filter that minimizes mean-square error between the desired signal and the filter output given knowledge of signal and noise statistics. Developed by Norbert Wiener in 1949, it provides the theoretical foundation for optimal filtering and remains the benchmark against which all other linear filtering methods are compared.
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ScholarGateمقایسهٔ روش‌ها: Power Spectral Density Estimation · Wiener Filter. بازیابی‌شده در 2026-06-18 از https://scholargate.app/fa/compare