A new method of signal description and its applications to signal processing

Zayezdny, A.; Druckmann, I.

doi:10.1016/0165-1684(91)90047-m

Cited by 17 publications

(3 citation statements)

References 7 publications

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“…The frequency estimation section of the EDM algorithm is obtained from the GDE of the composite signal invariant to the amplitudes [39]. Consequently, frequency demodulation in the EDM is independent of the MPR parameter.…”

Section: B Effect Of the Mean Power Ratio (Mpr) Parametermentioning

confidence: 99%

“…The structure of the block matrix corresponding to the intersection of the spans of the blocks and is therefore identical to that of any of the other blocks (only the dimension, , of the identity matrices is different). For the case of three arbitrary matrix blocks put together, the di-mension of the intersection of the spans of the column of each block, consequently, is given by (38) This intersection of the spans of the blocks can be generalized as (39) If is a sequence of subspaces in a finite dimensional vector space then it can be shown for the case of that [31]…”

Section: A Application To Cohannel and Adjacent Channel Separationmentioning

confidence: 99%

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Multicomponent AM-FM demodulation via periodicity-based algebraic separation and energy-based demodulation

Santhanam

Maragos

2000

IEEE Trans. Commun.

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Previously investigated multicomponent AM-FM demodulation techniques either assume that the individual component signals are spectrally isolated from each other or that the components can be isolated by linear time-invariant filtering techniques and, consequently, break down in the case where the components overlap spectrally or when one of the components is stronger than the other. In this paper, we present a nonlinear algorithm for the separation and demodulation of discrete-time multicomponent AM-FM signals. Our approach divides the demodulation problem into two independent tasks: algebraic separation of the components based on periodicity assumptions and then monocomponent demodulation of each component by instantaneously tracking and separating its source energy into its amplitude and frequency parts. The proposed new algorithm avoids the shortcomings of previous approaches and works well for extremely small spectral separations of the components and for a wide range of relative amplitude/power ratios. We present its theoretical analysis and experimental results and outline its application to demodulation of cochannel FM voice signals.

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Section: B Effect Of the Mean Power Ratio (Mpr) Parametermentioning

confidence: 99%

Section: A Application To Cohannel and Adjacent Channel Separationmentioning

confidence: 99%

Multicomponent AM-FM demodulation via periodicity-based algebraic separation and energy-based demodulation

Santhanam

Maragos

2000

IEEE Trans. Commun.

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“…Here, the parameter of interest E is referred to as the estimated parameter and the maximum, acceptable value of this parameter uncertainty, which is usually given or tacitly assumed, will be denoted as E ∆ . The procedure of the parameter estimation is always performed in circumstances of a preliminary knowledge of the investigated signal (see, e.g., [1][2][3][4][5][6]). This knowledge is usually composed of the set of individual information items.…”

Section: Introductionmentioning

confidence: 99%

The necessary condition for information usefulness in signal parameter estimation

Smołalski

Recent Advances in Mechatronics

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The entire knowledge available of the investigated signal has been represented as a set of specific constraints imposed in the signal space. The notion of the subsets' cluster was introduced and used for formulating the necessary condition for both direct and indirect usefulness of the given information item in estimating the needed parameter of the signal. Since the checking procedure for the presented necessary condition is quite simple, it seems to be a practical tool for elimination of useless information items.

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Extrapolation of time series by their structural properties

Zayezdny¹,

Tiunov²

1993

Signal Processing

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A new method of signal description and its applications to signal processing

Cited by 17 publications

References 7 publications

Multicomponent AM-FM demodulation via periodicity-based algebraic separation and energy-based demodulation

Multicomponent AM-FM demodulation via periodicity-based algebraic separation and energy-based demodulation

The necessary condition for information usefulness in signal parameter estimation

Extrapolation of time series by their structural properties

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