The Wigner distribution of noisy signals with adaptive time-frequency varying window
نویسندگان
چکیده
منابع مشابه
The Wigner distribution of noisy signals with adaptive time-frequency varying window
Time–frequency representations using the Wigner distribution (WD) may be significantly obscured by the noise in observations. The analysis performed for the WD of discrete-time noisy signals shows that this time–frequency representation can be optimized by the appropriate choice of the window length. However, the practical value of this analysis is not significant because the optimization requi...
متن کاملSuppressing the Cross Terms of the Wigner Distribution with an Adaptive Frequency Smoothing Window
A method for reducing the cross-terms in the WD with an adaptive frequency smoothing window is proposed in this paper. By using the short time Fourier spectrum of the input signal and some simple preprocessing steps, such as smoothing and peak labeling, the proposed method adaptively calculates the width of the frequency smoothing window. The simulation results of the linear frequency modulated...
متن کاملInstantaneous Frequency Estimation Using The Wigner Distribution With Varying And Data-driven Window - Signal Processing, IEEE Transactions on
Estimation of the instantaneous frequency (IF) of a harmonic complex-valued signal with an additive noise using the Wigner distribution is considered. If the IF is a nonlinear function of time, the bias of the estimate depends on the window length. The optimal choice of the window length, based on the asymptotic formulae for the variance and bias, can be used in order to resolve the bias-varian...
متن کاملTime-frequency analysis of FSK digital modulation signals using the smooth lag-windowed Wigner-Ville distribution
Digital modulation signals such as FSK are time-varying signals that can he represented in the time-frequency representation. The smooth lag-windowed Wigner-Ville distribution (SLWWVD) is proposed as a method to obtain accurate time-frequency representation of FSK signals used in HF (High Frequency) radio communications. Unlike existing time-frequency distributions such as the windowed Wigner-V...
متن کاملClustering Noisy Signals with Structured Sparsity Using Time-Frequency Representation
We propose a simple and efficient time-series clustering framework particularly suited for low Signalto-Noise Ratio (SNR), by simultaneous smoothing and dimensionality reduction aimed at preserving clustering information. We extend the sparse K-means algorithm by incorporating structured sparsity, and use it to exploit the multi-scale property of wavelets and group structure in multivariate sig...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Transactions on Signal Processing
سال: 1999
ISSN: 1053-587X
DOI: 10.1109/78.752607