AIMC Topic: Neural Networks, Computer

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Frame-by-frame language identification in short utterances using deep neural networks.

Neural networks : the official journal of the International Neural Network Society
This work addresses the use of deep neural networks (DNNs) in automatic language identification (LID) focused on short test utterances. Motivated by their recent success in acoustic modelling for speech recognition, we adapt DNNs to the problem of id...

Multistate network model for the pathfinding problem with a self-recovery property.

Neural networks : the official journal of the International Neural Network Society
In this study, we propose a continuous model for a pathfinding system. We consider acyclic graphs whose vertices are connected by unidirectional edges. The proposed model autonomously finds a path connecting two specified vertices, and the path is re...

Stability Analysis of Distributed Delay Neural Networks Based on Relaxed Lyapunov-Krasovskii Functionals.

IEEE transactions on neural networks and learning systems
This paper revisits the problem of asymptotic stability analysis for neural networks with distributed delays. The distributed delays are assumed to be constant and prescribed. Since a positive-definite quadratic functional does not necessarily requir...

Modeling the dynamics of evaluation: a multilevel neural network implementation of the iterative reprocessing model.

Personality and social psychology review : an official journal of the Society for Personality and Social Psychology, Inc
We present a neural network implementation of central components of the iterative reprocessing (IR) model. The IR model argues that the evaluation of social stimuli (attitudes, stereotypes) is the result of the IR of stimuli in a hierarchy of neural ...

A Spiking Neural Simulator Integrating Event-Driven and Time-Driven Computation Schemes Using Parallel CPU-GPU Co-Processing: A Case Study.

IEEE transactions on neural networks and learning systems
Time-driven simulation methods in traditional CPU architectures perform well and precisely when simulating small-scale spiking neural networks. Nevertheless, they still have drawbacks when simulating large-scale systems. Conversely, event-driven simu...

An Interval Type-2 Neural Fuzzy System for Online System Identification and Feature Elimination.

IEEE transactions on neural networks and learning systems
We propose an integrated mechanism for discarding derogatory features and extraction of fuzzy rules based on an interval type-2 neural fuzzy system (NFS)-in fact, it is a more general scheme that can discard bad features, irrelevant antecedent clause...

Exponential Stabilization of Memristor-based Chaotic Neural Networks with Time-Varying Delays via Intermittent Control.

IEEE transactions on neural networks and learning systems
This paper is concerned with the global exponential stabilization of memristor-based chaotic neural networks with both time-varying delays and general activation functions. Here, we adopt nonsmooth analysis and control theory to handle memristor-base...

Toward a new task assignment and path evolution (TAPE) for missile defense system (MDS) using intelligent adaptive SOM with recurrent neural networks (RNNs).

IEEE transactions on cybernetics
In this paper, a new adaptive self-organizing map (SOM) with recurrent neural network (RNN) controller is proposed for task assignment and path evolution of missile defense system (MDS). We address the problem of N agents (defending missiles) and D t...

Phase Oscillatory Network and Visual Pattern Recognition.

IEEE transactions on neural networks and learning systems
We explore a properly interconnected set of Kuramoto type oscillators that results in a new associative-memory network configuration, which includes second- and third-order additional terms in the Fourier expansion of the network's coupling. Investig...

On Equivalence of FIS and ELM for Interpretable Rule-Based Knowledge Representation.

IEEE transactions on neural networks and learning systems
This paper presents a fuzzy extreme learning machine (F-ELM) that embeds fuzzy membership functions and rules into the hidden layer of extreme learning machine (ELM). Similar to the concept of ELM that employed the random initialization technique, th...