Various biomedical research studies, such as large-population studies and studies on rare diseases, require sharing of data across multiple sources or institutions. In fact, data sharing will enable the collection of more cases for analysis and thus increase the statistical power of the study. However, combining data from various sources poses privacy risks. A number of protocols have been prop...

This paper presents distributed conjugate gradient (CG) algorithms for distributed parameter estimation and spectrum estimation over wireless sensor networks. In particular, distributed conventional conjugate gradient (CCG) and modified conjugate gradient (MCG) algorithms are developed with incremental and diffusion adaptive cooperation strategies. The distributed CCG and MCG algorithms have an...

| An algorithm is developed for the design of a nonlinear, n-sensor, distributed estimation system subject to communication and computation constraints. The algorithm uses only bivariate probability distributions and yields locally optimal estimators that satisfy the required system constraints. It is shown that the algorithm is a generalization of the classical Lloyd{Max results.

The knowledge about its operation environment is a fundamental requirement for intelligent agent acting in a dynamic world. Knowledge gathering is thus a critical functionality for any agents and it involves several problems: perception, object detection, environment structure reconstruction and so on. The state estimation problem is a general definition to describe many applications: object tr...

There are three important consequences from Theorem 6. Corollary 1: If Construction C is applied on the extended Hamming code of length 2”, we obtain an abnotmal (2”, 3)2 code. CoroZlary2: If Construction C is applied on the punctured Preparata code of length 2’”-1, we obtain an abnormal (2’”-1, 4)3 code. Corollary 3: If Construction C is applied on the Preparata code of length 22m, we obtain a...

Estimation is a canonical problem in sensor networks. The intrinsic nature of sensor networks requires estimation algorithms based on sensor data to be distributed and recursive; such algorithms are studied in this chapter for the problem of (conditional) least squares estimation. The chapter is divided into three parts. In the first part, distributed and recursive estimation algorithms are dev...

In this paper, we provide a distributed frequency offset estimation algorithm based on a variant of belief propagation (BP). Each agent in the network pre-compensates its carrier frequency individually so that there is no frequency offset from the desired carrier frequency between each pair of transceiver. The pre-compensated offset for each agent is computed in a distributed fashion in order t...

forecasting stock price had been paying attention to many analysts and stockholders. today, this issue more recent years has been do by new methods but new methods, good enough, not have analysis of description and changes effective variables on stock price whereas all this method rely on regression bases. ardl (autoregression distributed lag ) of one equation cumulative regression method obtai...