Ramdas Kumaresan - Academia.edu (original) (raw)
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Papers by Ramdas Kumaresan
Circuits, Systems and Signal Processing - Special Issue on Multivariable Systems, Nov 1, 1994
A theoretical and algorithmic framework is proposed for the identification of rational transfer f... more A theoretical and algorithmic framework is proposed for the identification of rational transfer function matrices of a class of discrete-time multivariable systems. The proposed technique obtains an optimal approximation from the given (possibly noisy) measured impulse response data. It is assumed that the measured impulse response data
corresponds to a system with a strictly proper transfer function matrix. The impulse response fitting error criterion is theoretically decoupled into a purely linear problem for estimating the optimal numerators and a nonlinear problem for the optimal denominators. Based on the proposed theoretical basis, an efficient computational algorithm is developed and illustrated with several examples.
ICASSP-98; IEEE International Conference on Acoustics, Speech and Signal Processing, Seattle, WA, May 1, 1998
Algorithms are presented for least-squares approximation of Toeplitz and Hankel matrices from no... more Algorithms are presented for least-squares approximation
of Toeplitz and Hankel matrices from noise corrupted
or ill-composed matrices, which may not have correct structural or rank properties. Utilizing Caratheodery's Theorem on complex number representation to model
the Toeplitz and Hankel matrices, it is shown that these
matrices possess specific row and column structures.
The inherent structures of the matrices are exploited
to develop a computational algorithm for estimation of
the matrices that are closest, in the Frobenius norm
sense, to the given noisy or rank-excessive matrices.
Simulation studies bear out the effectiveness of the proposed algorithms providing significantly better results
than the state-space methods.
Antennas and Propagation, IEEE …, Jan 1, 1988
ICASSP '87. IEEE International Conference on Acoustics, Speech, and Signal Processing, 1987
Estimation of angles of arrival of plane waves from data observed at an array of sensors is perfo... more Estimation of angles of arrival of plane waves from data observed at an array of sensors is performed with a network of interconnected, instantaneous, saturating non-linear elements called neurons. The networks use the observed data to decide which among a large number of hypothesized angles of arrivals best fits the data. A possible stochastic-digital implementation of such a network is
IEEE Transactions on Acoustics, Speech, and Signal Processing, 1988
Proceedings of the IEEE, 2000
Proceedings of the IEEE, 2000
ABSTRACT This work addresses the problem of identifying multiple fundamental frequencies in an ac... more ABSTRACT This work addresses the problem of identifying multiple fundamental frequencies in an acoustic signal. An auditoryinspired peripheral signal processing model is proposed that functions in a manner more like a bank of FM receivers rather than a ...
![Research paper thumbnail of Estimating the parameters of exponentially damped or undamped sinusoidal signals in noise[Technical Progress Report, Feb. 1981- Jul. 1982]](https://attachments.academia-assets.com/46214253/thumbnails/1.jpg)
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Circuits, Systems and Signal Processing - Special Issue on Multivariable Systems, Nov 1, 1994
A theoretical and algorithmic framework is proposed for the identification of rational transfer f... more A theoretical and algorithmic framework is proposed for the identification of rational transfer function matrices of a class of discrete-time multivariable systems. The proposed technique obtains an optimal approximation from the given (possibly noisy) measured impulse response data. It is assumed that the measured impulse response data
corresponds to a system with a strictly proper transfer function matrix. The impulse response fitting error criterion is theoretically decoupled into a purely linear problem for estimating the optimal numerators and a nonlinear problem for the optimal denominators. Based on the proposed theoretical basis, an efficient computational algorithm is developed and illustrated with several examples.
ICASSP-98; IEEE International Conference on Acoustics, Speech and Signal Processing, Seattle, WA, May 1, 1998
Algorithms are presented for least-squares approximation of Toeplitz and Hankel matrices from no... more Algorithms are presented for least-squares approximation
of Toeplitz and Hankel matrices from noise corrupted
or ill-composed matrices, which may not have correct structural or rank properties. Utilizing Caratheodery's Theorem on complex number representation to model
the Toeplitz and Hankel matrices, it is shown that these
matrices possess specific row and column structures.
The inherent structures of the matrices are exploited
to develop a computational algorithm for estimation of
the matrices that are closest, in the Frobenius norm
sense, to the given noisy or rank-excessive matrices.
Simulation studies bear out the effectiveness of the proposed algorithms providing significantly better results
than the state-space methods.
Antennas and Propagation, IEEE …, Jan 1, 1988
ICASSP '87. IEEE International Conference on Acoustics, Speech, and Signal Processing, 1987
Estimation of angles of arrival of plane waves from data observed at an array of sensors is perfo... more Estimation of angles of arrival of plane waves from data observed at an array of sensors is performed with a network of interconnected, instantaneous, saturating non-linear elements called neurons. The networks use the observed data to decide which among a large number of hypothesized angles of arrivals best fits the data. A possible stochastic-digital implementation of such a network is
IEEE Transactions on Acoustics, Speech, and Signal Processing, 1988
Proceedings of the IEEE, 2000
Proceedings of the IEEE, 2000
ABSTRACT This work addresses the problem of identifying multiple fundamental frequencies in an ac... more ABSTRACT This work addresses the problem of identifying multiple fundamental frequencies in an acoustic signal. An auditoryinspired peripheral signal processing model is proposed that functions in a manner more like a bank of FM receivers rather than a ...