Detection of signals by information theoretic criteria: general asymptotic performance analysis
نویسندگان
چکیده
Detecting the number of sources is a well-known and a well-investigated problem. In this problem, the number of sources impinging on an array of sensors is to be estimated. The common approach for solving this problem is to use an information theoretic criterion like the minimum description length (MDL), or the Akaike information criterion (AIC). Although it has been gaining much popularity and has been used in a variety of problems, the performance of information theoretic criteria-based estimators for the unknown number of sources has not been sufficiently studied, yet. In the context of array processing, the performance of such estimators were analyzed only for the special case of Gaussian sources where no prior knowledge of the array structure, if given, is used. Based on the theory of misspecified models, this paper presents a general asymptotic analysis of the performance of any information theoretic criterion-based estimator, and especially of the MDL estimator. In particular, the performance of the MDL estimator, which assumes Gaussian sources and structured array when applied to Gaussian sources, is analyzed. In addition, it is shown that the performance of a certain MDL estimator is not very sensitive to the actual distribution of the source signals. However, appropriate use of prior knowledge about the array geometry can lead to significant improvement in the performance of the MDL estimator. Simulation results show good fit between the empirical and the theoretical results.
منابع مشابه
SVD-based information theoretic criteria for detection of the number of damped/undamped sinusoids and their performance analysis
Recently, Wax and Kailath developed information theoretic criteria for detection of the number of signals received by a sensor array. More recently, Fuchs developed a criterion, based on the perturbation analysis of the data autocorrelation matrix, for detecting the number of sinusoids. In this paper, following the information theoretic approach to model selection, we first develop criteria for...
متن کاملEnergy Detection of Unknown Signals over Composite multipath/shadowing Fading Channels
In this paper, the performance analysis of an energy detector is exploited over composite multipath/shadowing fading channels, which is modeled by Rayleigh-lognormal (RL) distribution. Based on an approximate channel model which was recently proposed by the author, the RL envelope probability density function (pdf) is approximated by a finite sum of weighted Rayleigh pdfs. Relying on this inter...
متن کاملAsymptotic Analysis of Binary Gas Mixture Separation by Nanometric Tubular Ceramic Membranes: Cocurrent and Countercurrent Flow Patterns
Analytical gas-permeation models for predicting the separation process across membranes (exit compositions and area requirement) constitutes an important and necessary step in understanding the overall performance of membrane modules. But, the exact (numerical) solution methods suffer from the complexity of the solution. Therefore, solutions of nonlinear ordinary differential equations th...
متن کاملOptimized Seizure Detection Algorithm: A Fast Approach for Onset of Epileptic in EEG Signals Using GT Discriminant Analysis and K-NN Classifier
Background: Epilepsy is a severe disorder of the central nervous system that predisposes the person to recurrent seizures. Fifty million people worldwide suffer from epilepsy; after Alzheimer’s and stroke, it is the third widespread nervous disorder.Objective: In this paper, an algorithm to detect the onset of epileptic seizures based on the analysis of brain electrical signals (EEG) has b...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- IEEE Trans. Signal Processing
دوره 50 شماره
صفحات -
تاریخ انتشار 2002