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An introduction to statistical signal processing with applications
1. Introduction. 2. Signals and Systems. 3. Detection Theory. 4. Detection of Signals in Noise. 5. Estimation Theory. 6. Estimation of Waveforms. 7. Further Topics in Detection and Estimation. 8.Expand
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Impact of water supply on the incidence of diarrhoea and shigellosis among children in rural communities in Madurai.
-. Gastrointestinal diseases constitute a major public health problem in India, particularly among infants and pre-school children. The State Governments have been investing large funds under theExpand
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Optimum Linear Estimation of Stochastic Signals in the Presence of Multiplicative Noise
This paper considers optimum (MMSE) linear recursive estimation of stochastic signals in the presence of multiplicative noise in addition to measurement noise. Often problems associated withExpand
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Recognition of speech under stress and in noise
Speech recognizers trained in one condition but operating in a different condition degrade in performance. Typical of this situation is when the recognizer is trained under normal conditions butExpand
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Speech recognition in the F-16 cockpit using principal spectral components
A modification of the usual LPC speaker-dependent speech recognition algorithms yielded significantly improved recognition performance in an F-16 fighter cockpit environment.The LPC model is firstExpand
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Structure and Parameter Adaptive Pattern Recognition With Supervised Learning: A New Formulation
A new formulation of the problem of structure and parameter adaptive pattern recognition with supervised learning yielding significant computational advantages is presented.
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Free-text speaker identification over long distance telephone channel using hypothesized phonetic segmentation
Experimental investigation of a free-text speaker identification method based on long-term statistics was conducted on a widely used long-distance telephone database. On a 26-speaker subset, anExpand
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Estimation of randomly occurring stochastic signals in Gaussian noise (Corresp.)
This note applies the general likelihood ratio for the minimum-mean-square-error estimation of the signal when the presence of the signal at the receiver is uncertain during the entire observationExpand
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Unsupervised learning in nongaussian pattern recognition
Abstract This paper considers unsupervised learning, structure and parameter adaptive binary pattern recognition when a nongaussian pattern is observed in gaussian noise. Different schemes, none ofExpand
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