A New Fast Training Algorithm of the WTM Kohonen Neural Network Implemented for Classification of Biomedical Signals
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Ensuring correct network behavior is hard. This is the case even for simple networks, and adding middleboxes only complicates this task. In this paper, we demonstrate a fundamental property of networks. Namely, we show a way of using a network to emulate t ...
This work characterizes the nature of the limit point of distributed strategies for adaptation and learning over networks in the general case when the combination policy is not necessarily doubly stochastic and when the individual risks do not necessarily ...
This article presents the design and a first pilot evaluation of the computer-based training program Calcularis for children with developmental dyscalculia (DD) or difficulties in learning mathematics. The program has been designed according to insights on ...
In this work, we analyze the generalization ability of distributed online learning algorithms under stationary and non-stationary environments. We derive bounds for the excess-risk attained by each node in a connected network of learners and study the perf ...
Nature provides splendid examples of real-time learning and adaptation behavior that emerges from highly localized interactions among agents of limited capabilities. For example, schools of fish are remarkably apt at configuring their topologies almost ins ...
This paper presents a systematic computational study on the performance of distributed optimization in model predictive control (MPC). We consider networks of dynamically coupled systems, which are subject to input and state con- straints. The resulting MP ...
Adaptive networks rely on in-network and collaborative processing among distributed agents to deliver enhanced performance in estimation and inference tasks. Information is exchanged among the nodes, usually over noisy links. The combination weights that a ...
We propose an adaptive diffusion mechanism to optimize global cost functions in a distributed manner over a network of nodes. The cost function is assumed to consist of a collection of individual components. Diffusion adaptation allows the nodes to coopera ...
The paper presents a new CMOS implementation of the initialization mechanism for Kohonen self-organizing neural networks. A proper selection of initial values of the weights of the neurons exhibits a significant impact on the quality of the learning proces ...
In networks that perform linear network coding, an intermediate network node may receive a much larger number of linear equations of the source symbols than the number of messages it needs to send. For networks constructed by untrusted nodes, we propose a ...