The first purpose of this chapter is to review several TFRs defined in Table 4.1 and to describe many of the desirable properties listed in Table 4.2 that an ideal TFR should satisfy. TFRs will be grouped into classes satisfying similar properties to provide a more intuitive understanding of their similarities, advantages, and disadvantages. Further, each TFR within a given class is completely characterized by a unique set of kernels that provide valuable insight into whether or not a given TFR (1) satisfies other ideal TFR properties, (2) is easy to compute, and (3) reduces nonlinear cross-terms. The second goal of this chapter is to discuss applications of TFRs to signal analysis and detection problems in bioengineering. Unfortunately, no...
Spectral analysis is important in many fields, such as speech, radar and biomedicine. Many signals e...
In Applications in Time Frequency Signal Processing, ed. par A. Papandreou-Suppappola, CRC Press, pp...
Recent investigations have lead to the use of TFRs to filter noise-corrupted, frequency varying sign...
The first purpose of this chapter is to review several TFRs defined in Table 4.1 and to describe man...
Time-Frequency Signal Analysis and Processing (TFSAP) is a collection of theory, techniques and algo...
The main objective here is to use the time-frequency techniques for the analysis of biomolecular seq...
In this paper, a deconvolution approach based on time frequency representation (TFR) methods is used...
In our everyday life we are surrounded by phenomena whose spectral content varies as time evolves, s...
Signal processing offers a wide spectrum of theories, methods, and algorithms for addressing a varie...
The Fourier Transform is an ideal tool for representing and implementing shift-invariant linear syst...
Due to the non-stationary, multicomponent nature of biomedical signals, the use of time-frequency an...
This paper presents a tutorial review of recent advances in the field of time-frequency (t, f) signa...
Signal analysis is the process by which a signal is transformed into a representation which is meani...
This paper presents a tutorial review of recent advances in the field of time–frequency (t,f)(t,f) s...
Mixed time-frequency representations are transformations of time-varying signals that depict how the...
Spectral analysis is important in many fields, such as speech, radar and biomedicine. Many signals e...
In Applications in Time Frequency Signal Processing, ed. par A. Papandreou-Suppappola, CRC Press, pp...
Recent investigations have lead to the use of TFRs to filter noise-corrupted, frequency varying sign...
The first purpose of this chapter is to review several TFRs defined in Table 4.1 and to describe man...
Time-Frequency Signal Analysis and Processing (TFSAP) is a collection of theory, techniques and algo...
The main objective here is to use the time-frequency techniques for the analysis of biomolecular seq...
In this paper, a deconvolution approach based on time frequency representation (TFR) methods is used...
In our everyday life we are surrounded by phenomena whose spectral content varies as time evolves, s...
Signal processing offers a wide spectrum of theories, methods, and algorithms for addressing a varie...
The Fourier Transform is an ideal tool for representing and implementing shift-invariant linear syst...
Due to the non-stationary, multicomponent nature of biomedical signals, the use of time-frequency an...
This paper presents a tutorial review of recent advances in the field of time-frequency (t, f) signa...
Signal analysis is the process by which a signal is transformed into a representation which is meani...
This paper presents a tutorial review of recent advances in the field of time–frequency (t,f)(t,f) s...
Mixed time-frequency representations are transformations of time-varying signals that depict how the...
Spectral analysis is important in many fields, such as speech, radar and biomedicine. Many signals e...
In Applications in Time Frequency Signal Processing, ed. par A. Papandreou-Suppappola, CRC Press, pp...
Recent investigations have lead to the use of TFRs to filter noise-corrupted, frequency varying sign...