integrate and fire model#rate model#conductance models#synaptic model#multicompartment model integrate and fire model leaky integrate and fire model rate model synaptic input to the integrate and fire model conductance models kinetic models of ionic channels synaptic input to conductance models models of synaptic modification multicompartmental models This is an article that describes realistic...

This paper uses a simple modification of classic Kohonen network (SOM), which allows parallel processing of input data vectors or partitioning the problem in case of insufficient resources (memory, disc space, etc.) to process all input vectors at once. The algorithm has been implemented to meet a specification of modern multicore graphics processors to achieve massive parallelism. The algorith...

An adaptive fuzzy inference neural network (AFINN) is proposed in this paper. It has self-construction ability, parameter estimation ability and rule extraction ability. The structure of AFINN is formed by the following four phases: (1) initial rule creation, (2) selection of important input elements, (3) identification of the network structure and (4) parameter estimation using LMS (least-mean...

A technique is described that permits the on-line construction and dynamic modification of parse trees during the processing of sentence-like input. The approach is a combination of simple recurrent network (SRN) and recursive auto-associative memory (RAAM) . The parsing technique involves teaching the SRN to build RAAM representations as it processes its input item-by-item. The approach is a p...

A technique is described that permits the on-line wnstruction and dynamic modification of parse trees during the processing of sentence-like input. The approach is a combination of simple recurrent network (SRN) and recursive auto-asson'ative memory (IUAM). The parsing technique involves teaching the SRN to build RUM representations as it processes its input item by item. The approach is a pote...

A novel approach to speech coding is introduced in this paper for the coding of speech signals used in vocoders. While conventional methods code the original input speech signal, the proposed algorithm codes the timescale modified signal instead. In this method, the transmitter speeds up original input speech signal by a factor of beta using waveform similarity overlap-addmethod (WSOLA). This s...

Activity-dependent synaptic plasticity is classically though to be the cellular substrate for learning and memory. Recent data show that activation of glutamate receptors initiates a long-term modification in pre- or post-synaptic neuronal excitability. Similarly to synaptic plasticity, intrinsic plasticity is bidirectional and input- or cell-specific. In addition to an increase in the reliabil...

An algorithm for the adaptive stabilization of single-input single-output time-varying first-order discretctimc systems is presented. Only the knowledge of the sign of the feedback gain and an upper bound of it is rcquired. The adaptive control law is robust with rcspect to nonlinear additive time-varying state, input and output perturbations_ I f the s ign of the feedback gain is not known, i ...

For a class of linear dynamical systems with unknown parameters a direct model reference adaptive control framework is developed that provides stable adaptation in the presence of input constraints. The proposed design methodology, termed “positive μ-modification”, protects the control law from actuator position saturation. Moreover, the design is Lyapunov based and ensures global asymptotic tr...

This paper deals with path-wise performance analysis rather than a nodal one to enrich results previously obtained in the literature under simple but unsatisfactory assumptions, e.g., Poisson processes. First deriving the per-stream loss probability, delay, and delay variance of an isolated queue with multi-class input streams modeled by heterogeneous two-state Markovmodulated Poisson processes...