This paper surveys the recent developments in the area of equalization of the wireless propagation channels. It focuses on a subclass of equalization algorithms that minimizes the Mean Square Error (MMSE) between the desired and estimated signal. The following aspects of the equalization problem are considered: system modeling, algorithm classification based on the availability of training sequ...

We propose a new class of dimension reduction methods using the first two inverse moments, called Sliced Inverse Moment Regression (SIMR). We develop corresponding weighted chi-squared tests for the dimension of the regression. Basically, SIMR are linear combinations of Sliced Inverse Regression (SIR) and the method using a new candidate matrix which is designed to recover the entire inverse se...

This paper outlines the clinical doctoral research plan (funded by HEE/NIHR Integrated Clinical Academic Programme) to engage the wide range of people who use alternative and augmentative communication (AAC) to understand the perspectives of users in order to develop a Patient Reported Outcome Measure (PROM) to evaluate equipment and services.

This paper studies nonparametric estimation of conditional moment models in which the generalized residual functions can be nonsmooth in the unknown functions of endogenous variables. This is a nonparametric nonlinear instrumental variables (IV) problem. We propose a class of penalized sieve minimum distance (PSMD) estimators which are minimizers of a penalized empirical minimum distance criter...

1 This paper studies nonparametric estimation of conditional moment restrictions in which the generalized residual functions can be nonsmooth in the unknown functions of endogenous variables. This is a nonparametric nonlinear instrumental variables (IV) problem. We propose a class of penalized sieve minimum distance (PSMD) estima-tors, which are minimizers of a penalized empirical minimum dista...

Within image analysis the distance transform has many applications. The distance transform measures the distance of each object point from the nearest boundary. For ease of computation, a commonly used approximate algorithm is the chamfer distance transform. This paper presents an efficient linear-time algorithm for calculating the true Euclidean distance-squared of each point from the nearest ...

The deconvolution in image processing is an inverse illposed problem which necessitates a trade-off between delity to data and smoothness of a solution adjusted by a regularization parameter. In this paper we propose two techniques for selection of a varying regularization parameter minimizing the mean squared error for every pixel of the image. The rst algorithm uses the estimate of the square...

CHI-SQUARED DISTANCE AND METAMORPHIC VIRUS DETECTION by Annie H. Toderici Malware are programs that are designed with a malicious intent. Metamorphic malware change their internal structure each generation while still maintaining their original behavior. As metamorphic malware become more sophisticated, it is important to develop efficient and accurate detection techniques. Current commercial a...