Nowadays, the usage of load emulators, is the best method for implementation and analysis of different electrical load change scenarios in laboratories. This paper presents an improved programmable load emulator which can emulate both reference active and reactive power simultaneously. The proposed control system can track the dynamic load changes rapidly and accurately in addition to pulse cha...

There have been several attempts to mathematically understand neural networks and many more from biological and computational perspectives. The field has exploded in the last decade, yet neural networks are still treated much like a black box. In this work we describe a structure that is inherent to a feed forward neural network. This will provide a framework for future work on neural networks ...

Coordinated patterns of precisely timed action potentials (spikes) emerge in a variety of neural circuits but their dynamical origin is still not well understood. One hypothesis states that synchronous activity propagating through feed-forward chains of groups of neurons (synfire chains) may dynamically generate such spike patterns. Additionally, synfire chains offer the possibility to enable r...

We study semi-infinite and bi-infinite scalar feed-forward networks. We find that the temporal dynamics of these systems is closely linked to the spatial dynamics of an associated interval map and show how this interval map may be used to describe stationary interfaces. Beyond stationary structures, we show that the onset of instabilities in finite networks is intimately related to the emergenc...

In [18] the authors developed a method for computing normal forms of dynamical systems with a coupled cell network structure. We now apply this theory to one-parameter families of homogeneous feed-forward chains with 2-dimensional cells. Our main result is that Hopf bifurcations in such families generically generate branches of periodic solutions with amplitudes growing like ∼ |λ| 1 2 ,∼ |λ| 1 ...

Visual Understanding is an increasing field of research thanks to the advances in image processing, object detection, classification, and advanced computational intelligence techniques. Hidden Markov Models (HMM) are one of these techniques which have been used extensively for this problem. This paper will introduce a new type of HMM, called Evidence Feed Forward Hidden Markov Models, that not ...

Microelectrode arrays (MEAs) are a promising new method for high throughput neuronal assays. These arrays permit non-invasive, detailed optical and multichannel electrophysiological interrogation of functional neuronal networks for drug development or neurotoxicity assessment. There has also been an effort by a number of groups to develop in vitro analogues of in vivo brain circuitry or physiol...

We present an algorithm to extract representations from multiple hidden layer, multiple output feedforward perceptron threshold networks. The representation is based on polytopic decision regions in the input space{ and is exact not an approximation like most other network analysis methods. Multiple examples show some of the knowledge that can be extracted from networks by using this algorithm,...

A prominent feature of gene transcription regulatory networks is the presence in large numbers of motifs, i.e., patterns of interconnection, in the networks. One such motif is the feed forward loop (FFL) consisting of three genes X, Y and Z. The protein product x of X controls the synthesis of protein product y of Y. Proteins x and y jointly regulate the synthesis of z proteins from the gene Z....

An overview of the current literature reveals a richness and complexity of anatomical, pharmacological and physiological features of the input systems to the archicortex. Evidence is cited to demonstrate that several afferent paths terminate on and directly excite hippocampal formation interneurons ("non-principal" cells) besides their contacts with pyramidal and granule cells (principal cells)...