In a detection&#10 network, the final decision is made by fusing the decisions from local detectors. The objective of that decision is to minimize the final error probability. To implement and optimal fusion rule, the performance of each detector, i.e. its probability of false alarm and its probability of missed detection as well as the a priori probabilities of the hypotheses, must be known. H...

providing a high-quality service for transmission and playing real-time voice conversations (voice streaming) over wireless ad-hoc networks is no mean feat. buffering together with adjusting the playout time of the packets is a receiver-side solution to overcome this challenge. in this paper, a new adaptive playout adjustment algorithm is proposed to stream the voice conversations over wireless...

increases in incidents involving so-called confused persons have brought attention to the potential costs of recent changes to public mental health (pmh) services in the netherlands. decentralized under the (community) participation act (2014), local governments must find resources to compensate for reduced central funding to such services or “innovate.” but innovation, even when pressure for c...

in a mobile ad hoc network, there are some features such as the ability to exploit multipath effect for information exchange with high reliability and low error rate. dealing with the aggressors and discovering the path in data transmission are of importance. approaching these goals ends in network promotion and efficiency. in this paper, the designed protocol is able to discover multipath fo...

an adaptive version of growing and pruning rbf neural network has been used to predict the system output and implement linear model-based predictive controller (lmpc) and non-linear model-based predictive controller (nmpc) strategies. a radial-basis neural network with growing and pruning capabilities is introduced to carry out on-line model identification.an unscented kalman filter (ukf) algor...

Robust adaptive estimation of unknown parameter has been an important issue in recent years for reliable operation in the distributed networks. The conventional adaptive estimation algorithms that rely on mean square error (MSE) criterion exhibit good performance in the presence of Gaussian noise, but their performance drastically decreases under impulsive noise. In this paper, we propose a rob...

In a detection network, the final decision is made by fusing the decisions from local detectors. The objective of that decision is to minimize the final error probability. To implement and optimal fusion rule, the performance of each detector, i.e. its probability of false alarm and its probability of missed detection as well as the a priori probabilities of the hypotheses, must be known. How...

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...

There are some experiences that researcher come across quite number of time for very large networks in the initial samples such that they cannot finish the sampling procedure. Two solutions have been proposed and used by marine biologists which we discuss in this article: i) Adaptive cluster sampling based on order statistics with a stopping rule, ii) Restricted adaptive cluster sampling. Until...