E-M ALGORITHMS FOR ESTIMATING PARAMETERS FROM SINGLE-MEMORY MARKOV POINT-PROCESSES HAVING A MULTIPLICATIVE INTENSITY.

Michael I. Miller; Neophytos A. Karamanos; Walter R. Bosch

E-M ALGORITHMS FOR ESTIMATING PARAMETERS FROM SINGLE-MEMORY MARKOV POINT-PROCESSES HAVING A MULTIPLICATIVE INTENSITY.

Michael I. Miller, Neophytos A. Karamanos, Walter R. Bosch

Division of Clinical Research

Research output: Contribution to journal › Conference article › peer-review

1 Scopus citations

Abstract

The probability that a neuron in the peripheral auditory nervous system discharges during some specified time interval depends on both a stimulus function and on effects due to earlier discharge events. With the objective of estimating parameters related to the stimulus function which are free from the distortion introduced by effects due to previous discharges, a maximum-likelihood estimation scheme has been developed. We have chosen a multiplicative intensity model to describe auditory-nerve discharges in which the intensity of the process is stochastic and the product of two functions: one an unknown deterministic function corresponding to the stimulus, and the second a stochastic function which is on the history of the process. Only abstract is given.

Original language	English
Pages (from-to)	370-371
Number of pages	2
Journal	Proceedings - Annual Allerton Conference on Communication, Control, and Computing
State	Published - Dec 1 1985

Cite this

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abstract = "The probability that a neuron in the peripheral auditory nervous system discharges during some specified time interval depends on both a stimulus function and on effects due to earlier discharge events. With the objective of estimating parameters related to the stimulus function which are free from the distortion introduced by effects due to previous discharges, a maximum-likelihood estimation scheme has been developed. We have chosen a multiplicative intensity model to describe auditory-nerve discharges in which the intensity of the process is stochastic and the product of two functions: one an unknown deterministic function corresponding to the stimulus, and the second a stochastic function which is on the history of the process. Only abstract is given.",

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year = "1985",

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E-M ALGORITHMS FOR ESTIMATING PARAMETERS FROM SINGLE-MEMORY MARKOV POINT-PROCESSES HAVING A MULTIPLICATIVE INTENSITY. / Miller, Michael I.; Karamanos, Neophytos A.; Bosch, Walter R.
In: Proceedings - Annual Allerton Conference on Communication, Control, and Computing, 01.12.1985, p. 370-371.

Research output: Contribution to journal › Conference article › peer-review

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AU - Bosch, Walter R.

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AB - The probability that a neuron in the peripheral auditory nervous system discharges during some specified time interval depends on both a stimulus function and on effects due to earlier discharge events. With the objective of estimating parameters related to the stimulus function which are free from the distortion introduced by effects due to previous discharges, a maximum-likelihood estimation scheme has been developed. We have chosen a multiplicative intensity model to describe auditory-nerve discharges in which the intensity of the process is stochastic and the product of two functions: one an unknown deterministic function corresponding to the stimulus, and the second a stochastic function which is on the history of the process. Only abstract is given.

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E-M ALGORITHMS FOR ESTIMATING PARAMETERS FROM SINGLE-MEMORY MARKOV POINT-PROCESSES HAVING A MULTIPLICATIVE INTENSITY.

Abstract

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