We propose a new recognition model called Concurrent Neural Networks (CNN), representing a winner-takes-all collection of neural networks. Each network of the system is trained individually to provide best results for one class only. We have applied the above model for the task of speaker recognition. We performed distinct speaker recognition experiments using three variants of basic components...

high processing loads, need for complicated and frequent updating, and high false alarm are some of the challenges in designing anomaly detection and misuse detection systems. we propose a new network-based intrusion detection system (ids) that resolves such shortcomings. our scheme fuses anomaly detection and misuse detection systems, which has not been utilized so far in existing systems. in ...

Along with an increase of the automobile possession quantity, the air pollution caused by the pollutant of the automobile emissions is serious day by day. The emission diagnosis become the important technology for guaranteeing the human sustainable development. The article introduces the reasons of CH excessive emissions in vehicle discharge of pollutants, the impact which CH excessive emission...

BACKGROUND Advances in "omics" technologies have revolutionized the collection of biological data. A matching revolution in our understanding of biological systems, however, will only be realized when similar advances are made in informatic analysis of the resulting "big data." Here, we compare the capabilities of three conventional and novel statistical approaches to summarize and decipher the...

Speaker verification is an active research problem that has been addressed using a variety of different classification techniques. However, in general, methods inspired by the human auditory system tend to show better verification performance than other methods. In this thesis three biologically inspired speaker verification algorithms are presented. The first is a vowel-dependent speaker verif...

In this paper we present a novel cognitive robotic model to study language acquisition in autonomous robots through the grounding of words in sensorimotor representations. The aim of this new model is to extend previous work on language grounding in simulated cognitive agents to the new robotic platform iCub. The iCub is an emerging open platform for cognitive robotic research that will allow r...

Asperger Syndrome is an autism spectrum disorder that reduces a patient’s ability to interact socially, and restricts their interests and abilities. Using functional magnetic resonance imaging (fMRI), it has been shown that Asperger patients exhibit reduced activity between the nodes of a resting-state neuronal network comprised of the posterior cingulate cortex (PCC), the medial prefrontal cor...

The method of self-organizing maps (SOM) is a method of exploratory data analysis used for clustering and projecting multi-dimensional data into a lower-dimensional space to reveal hidden structure of the data. The Self-Organizing Feature Maps (SOFMs) [11] is a class of neural networks capable of recognizing the main features of the data they are trained on. There is extensive literature on its...