Showing papers by "Andreas Spanias published in 1989"

Accurate representation of time-varying signals using mixed transforms with applications to speech

Abstract: Basis functions from two transforms, the discrete Fourier transform (DFT) and the Walsh-Hadamard transform are used. An iterative algorithm to implement the mixed representation is developed. A finite number of DFT components, either fixed or variable, is used to represent the selective (narrowband) dominant spectrum of the signal on a frame-by-frame basis. The whitened (broadband) residual signal is represented using a small number of Walsh components. The mixed partial sets are applied to speech representation. Preliminary results and informal listening using this model produced good quality speech. >

Efficient modeling of dominant transform components representing time-varying signals

Abstract: The mixed transform representation of time-varying signals uses partial sets of basis functions from the discrete Fourier transform (DFT) and the Walsh-Hadamard transform. The location, magnitude, and phase of the transform components have to be specified for proper signal reconstruction. A least-squares IIR (infinite impulse response) algorithm, in the transformed domains, which fits each of the retained subsets of the complex transform components accurately, is presented. The IIR function, while characterized by real coefficients about twice the number of the retained complex transform components, carries enough location, magnitude, and phase information for accurate signal reconstruction. To illustrate the technique's accuracy and efficiency, its application to model the DFT part of a voice speech segment is given. >

Direct coding of a class of non-stationary signals based on mixed transforms

Abstract: A mixed Fourier-Walsh signal representation is proposed for transform coding. Basis functions from two transforms are used, namely, the discrete Fourier transform (DFT) and the Walsh-Hadamard transform (WHT). An iterative algorithm is used to implement the mixed representation. A finite number of DFT components is used to represent the selective (narrowband) dominant spectrum of speech on a frame-by-frame basis. The whitened (broadband) residual signal is represented using a small number of Walsh components. The parameters of the mixed representation are coded directly by coding the DFT and WHT components. Results are given for frame-by-frame and packet coding at rates ranging from 16 kb/s to 9.6 kb/s. >

Fourier-Walsh representation of a class of non-stationary signals

Abstract: An approach that uses mixed partial sets of basis functions is proposed for time-varying signal representation. Basis functions from two transforms are used, namely the discrete Fourier transform (DFT) and the Walsh-Hadamard transform (WHT). An iterative algorithm is developed to implement the mixed representation. A finite number of DFT components, either fixed or variable, is used to represent the selective (narrowband) dominant spectrum of the signal on a frame-by-frame basis. The whitened (broadband) residual signal is represented using a small number of Walsh components. The mixed partial sets are applied to speech representation. Preliminary results and informal listenings using this model produced good quality speech. >