We propose a general modeling and algorithmic framework for discrete structure recovery that can be applied to wide range of problems. Under this framework, we are able study the clustering labels, ranks players, signs regression coefficients, cyclic shifts even group elements from unified perspective. A simple iterative algorithm is proposed recovery, which generalizes methods including Lloyd’...

A novel hybrid method for tracking multiple indistinguishable maneuvering targets using a wireless sensor network is introduced in this paper. The problem of tracking the location of targets is formulated as a Maximum Likelihood Estimation. We propose a hybrid optimization method, which consists of an iterative and a heuristic search method, for finding the location of targets simultaneously. T...

A new iterative learning controller is proposed for a general unknown discrete time-varying nonlinear non-affine system represented by NARMAX (Nonlinear Autoregressive Moving Average with eXogenous inputs) model. The proposed controller is composed of an iterative learning neural identifier and an iterative learning controller. Iterative learning control and iterative learning identification ar...

Adaptive networks include a set of nodes with adaptation and learning abilities for modeling various types of self-organized and complex activities encountered in the real world. This paper presents the effect of heterogeneously distributed incremental LMS algorithm with ideal links on the quality of unknown parameter estimation. In heterogeneous adaptive networks, a fraction of the nodes, defi...

Institutional review board approval and informed consent were obtained for this HIPAA-compliant study. The purpose was to prospectively compare multiecho iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL) gradient-echo (GRE) magnetic resonance (MR) imaging with three-dimensional fat-suppressed (FS) spoiled GRE (SPGR) MR imaging to evaluate the arti...

In the field of information forensics, many emerging problems involve a critical step that estimates and tracks weak frequency components in noisy signals. It is often challenging for prior art tracking to i) achieve high accuracy under conditions, ii) detect track multiple efficiently, or iii) strike good trade-off processing delay versus resilience tracking. To address these issues, we propos...

a new class of nonlinear set-valued variationalinclusions involving $(a,eta)$-monotone mappings in a banachspace setting is introduced, and then based on the generalizedresolvent operator technique associated with$(a,eta)$-monotonicity, the existence and approximationsolvability of solutions using an iterative algorithm and fixedpint theory is investigated.

In Speech processing Signal to Noise (SNR )Ratio plays an important role for Noise cancellation. here an attempt is made to evaluate SNR for given Noisy Speech signal using adaptive technique Binary LMS algorithm. In this proposal , Introduces the two control parameters of the Adaptive Algorithm rather than one control parameter as in case of LMS Algorithm. Also comparirison is made with respec...