The paper proposes a general framework which encompasses the training of neural networks and the adaptation of filters. We show that neural networks can be considered as general non-linear filters which can be trained adaptively, i. e. which can undergo continual training with a possibly infinite number of time-ordered examples. We introduce the canonical form of a neural network. This canonica...

Adaptive networks are complex networks with nontrivial topological features and connection patterns between their elements which are neither purely regular nor purely random. Their applications are in sociology, biology, physics, genetics, epidemiology, chemistry, ecology, materials science, the traditional Internet and the emerging Internet-of-Things. For example, their applications in sociolo...

. Non linrea distortion introduced by communications channels increases the probability of error. Application of artificial neural network structures to the problem of channel equalizationin a digital communication system has been considered in this paper. The difficulties associated with channel non linearities can be overcome by equalizers employing diagonal recurrent neural network (DRNN). B...

Energy efficient protocol design is the aim of current researches in the area of sensor networks where limited power resources impose energy conservation considerations. In this paper we care for Medium Access Control (MAC) protocols and after an extensive literature review, two adaptive schemes are discussed. Of them, adaptive-rate MACs which were introduced for throughput enhancement show the...

a digital look-up table adaptive predistortion technique using a six-port receiver for power amplifier linearization is presented. the system is designed in ka-band for a dvb-s2 satellite link. we use a six-port receiver at the linearizationloop in place of classic heterodyne receivers. the six-port receiver is implemented by the use of passive microwavecircuits and detector diodes. this approa...

there are two dominant approaches to describe and understand the anatomy of complete health and well-being systems internationally. yet, neither approach has been able to either predict or explain occasional but dramatic crises in health and well-being systems around the world and in developed emerging market or developing country contexts. as the impacts of such events can be measured not simp...

in this paper, the advantage of reinforcement learning to develop a new traffic shaper is invoked in order to obtain a reasonable utilization of bandwidth while preventing traffic overload in other parts of the network. this leads to a reduction in the total number of packet droppings in the whole network. the method is implemented in a novel proposed intelligent simulation environment. keeping...