نتایج جستجو برای: maximum likelihood sequence estimation

تعداد نتایج: 980561  

1998
Sergio Barbarossa Anna Scaglione

In this work we propose a novel ap roach for demodulating Continuous Phase Modulation CPM) signals based Q on the modeling of the instantaneous phase as a piecewise polynomial-phase function. The polynomial modeling can be a good approximation for currently used modulations or it can be-exact if the shaping pulse is chosen to be a oiecewise polvnomial function. The crucial step in the demodulat...

Journal: :Methods in molecular biology 2007
Dennis P Wall Todd Deluca

All protein coding genes have a phylogenetic history that when understood can lead to deep insights into the diversification or conservation of function, the evolution of developmental complexity, and the molecular basis of disease. One important part to reconstructing the relationships among genes in different organisms is an accurate method to find orthologs as well as an accurate measure of ...

1997
Boon Chong Ng Suhas N. Diggavi Arogyswami Paulraj

This paper describes an adaptive maximum likelihood sequence estimation (MLSE) receiver based on a structured linear channel model. Speciically, known prior information about the transmit lter is used to obtain a structured channel model linearly parameterized by a time-varying vector. We show that the total oversampled FIR channel vector lies within the subspace of a matrix associated only wit...

2001
Joan Bas Ana I. Pérez-Neira

The Maximum Likelihood Sequence Estimator (MLSE) and the Bayesian detector provide the best performance (at BER sense) under a data sequence or a symbol-by-symbol detection philosophy, respectively [1]. However, these detectors present a high computational burden and are quite unaffordable for a mobile terminal that exploits also the spatial diversity. To overcome this problem Fuzzy Logic has b...

2004
Roberto Cusani Jari Mattila

A transmissiodequalisation strategy is proposed for frequency-selective, fast time-varying noisy digital channels. Each information data sequence is surrounded by a pair of training sequences of known symbols; these are employed by the receiver to estimate the channel impulse response (CIR) at the beginning and at the end of the timeslot, via a suitable Kalman-like filter with fast convergence ...

2004
R. K. Martin

Channel shortening is often necessary for demodulation of multicarrier signals and complexity reduction of maximum likelihood sequence estimation (MLSE). This paper has two parts: (i) the proposal of complexity-reduction techniques for channel shortening designs with polynomial weighting functions, including the minimum inter-block interference (Min-IBI) and minimum delay spread (MDS) designs, ...

2006
Deepankar Basu Robert de Jong Anjan Mukherji Alita Nandi Randy Olsen G. V. Ravindra

This paper draws out some implications of son targeting fertility behaviour for gender inequality. It is demonstrated that such behaviour has two notable implications at the aggregate level: (a)larger number of siblings for girls (Sibling Effect), and (b)a higher within-family birth order for boys (Birth Order Effect). While the first tends to worsen gender inequality through monetary factors, ...

Journal: :Journal of the Royal Statistical Society. Series B, Statistical methodology 2014
Pavel N Krivitsky Mark S Handcock

Models of dynamic networks - networks that evolve over time - have manifold applications. We develop a discrete-time generative model for social network evolution that inherits the richness and flexibility of the class of exponential-family random graph models. The model - a Separable Temporal ERGM (STERGM) - facilitates separable modeling of the tie duration distributions and the structural dy...

2016
Kwun Chuen Gary Chan Jing Qin

We study nonparametric maximum likelihood estimation for the distribution of spherical radii using samples containing a mixture of one-dimensional, two-dimensional biased and three-dimensional unbiased observations. Since direct maximization of the likelihood function is intractable, we propose an expectation-maximization algorithm for implementing the estimator, which handles an indirect measu...

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