Conference PaperConventional signal processing typically involves frequency selective techniques which are highly inadequate for nonstationary signals. In this paper, we present an approach to perform time-frequency selective processing using the Wavelet Transform. The approach is motivated by the excellent localization, in both time and frequency, afforded by the wavelet basis functions. Suitably chosen wavelet basis functions are used to characterize the subspace of signals that have a given localized time-frequency support, thus enabling a time-frequency partitioning of signals. A practical implementation scheme using filter banks is also presented, and the effectiveness of the approach over conventional techniques is demonstrated
Abstract. In many applications such as parameter identification of oscillating systems in civil engi...
Like the Fourier Transform, the Wavelet Transform decomposes signals as a superposition of simple un...
Recent trends in signal processing have led to the discovery and implementation of wavelets as tools...
The aim of the data analysis is to explore the main characteristics of the signal by a signal transf...
We present a selective overview of time-frequency analysis and some of its key problems. In particul...
Orthonormal bases of wavelets and wavelet packets yield linear, non-redundant time-scale and time-fr...
Signals consisting of multiple frequencies and changing their amplitude while propagating in time ge...
A new representation of the Fourier transform in terms of time and scale localization is discussed t...
We consider the following pair of problems related to orthonormal compactly supported wavelet expans...
A traditional frequency analysis is not appropriate for observation of properties of non-stationary ...
Abstract. A method to analyse and filter real-valued discrete signals of finite duration s(n), n = 0...
A series of observations indexed in time often exhibits patterns that may serve as bases for allocat...
As a new signal processing tool, a Modified frequency slice wavelet transform (MFSWT) is proposed fo...
A method to analyse and filter real-valued discrete signals of finite duration s(n), n=0,1,...,N-1, ...
Time analysis and frequency analysis are both well-established ways in engineering to gain more know...
Abstract. In many applications such as parameter identification of oscillating systems in civil engi...
Like the Fourier Transform, the Wavelet Transform decomposes signals as a superposition of simple un...
Recent trends in signal processing have led to the discovery and implementation of wavelets as tools...
The aim of the data analysis is to explore the main characteristics of the signal by a signal transf...
We present a selective overview of time-frequency analysis and some of its key problems. In particul...
Orthonormal bases of wavelets and wavelet packets yield linear, non-redundant time-scale and time-fr...
Signals consisting of multiple frequencies and changing their amplitude while propagating in time ge...
A new representation of the Fourier transform in terms of time and scale localization is discussed t...
We consider the following pair of problems related to orthonormal compactly supported wavelet expans...
A traditional frequency analysis is not appropriate for observation of properties of non-stationary ...
Abstract. A method to analyse and filter real-valued discrete signals of finite duration s(n), n = 0...
A series of observations indexed in time often exhibits patterns that may serve as bases for allocat...
As a new signal processing tool, a Modified frequency slice wavelet transform (MFSWT) is proposed fo...
A method to analyse and filter real-valued discrete signals of finite duration s(n), n=0,1,...,N-1, ...
Time analysis and frequency analysis are both well-established ways in engineering to gain more know...
Abstract. In many applications such as parameter identification of oscillating systems in civil engi...
Like the Fourier Transform, the Wavelet Transform decomposes signals as a superposition of simple un...
Recent trends in signal processing have led to the discovery and implementation of wavelets as tools...