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This paper presents an event-driven categorization system which processes the address events from a Dynamic Vision Sensor. Using neuromorphic processing, cortex-like spike-based features are extracted by an event-driven MAX-like convolutional network. The extracted spike patterns are then classified by an Online Sequential Extreme Learning Machine with Auto Encoder. Using a Lookup Table, we achieve...
In the paper, the architecture of a pre-radical basis function(RBF) with deep back propagation(BP) neural network is proposed. The three-layer RBF network is altered into a two-layer RBF, the output of RBF hidden layer is processed and then connected with a multilayer perceptron network. Firstly, the input samples go through RBF hidden units and are pre-trained via unsupervised learning, after the...
In cognitive radio networks (CRNs), the cognitive Engine (CE) is responsible for decision making. This is quite a challenging task as it requires finding the balance between prediction accuracy and efficient learning for optimal configuration settings for the CRN. Artificial neural networks (ANNs) have been widely used as predictive tools in cognitive radio. In this paper, random neural networks (RNNs)...
The design of Artificial Neural Network (ANN) is a typical task as it is depends on human experience. There are few techniques like the Back-Propagation algorithm and nature inspired meta-heuristic are one of the most widely used and popular technique for optimizing feed forward neural network training. Artificial Bee Colony (ABC) algorithm is nature inspired meta-heuristic approach based on behavior...
The writer adaptation arisen with the appearance and the excessive use of Handheld devices. These devices are conceived to be used in diverse user settings which can be stationary or mobile. Most of the works tackle the writer adaptation in the "sitting at a desk" environment, nevertheless we notice a lack of contributions in the multi-environment context. In this paper we present a multi-environment...
Script identification from a document image is a complex real life problem in a multi-script country like India. The work becomes more challenging when handwritten documents are considered. In this paper, a Gabor filter based technique has been developed for offline script identification from handwritten document images. The work is carried out at document level on four popular Indic scripts namely...
Spike sorting is a fundamental preprocessing step for many neuroscience studies which rely on the analysis of spike trains. In this paper, we present two unsupervised spike sorting algorithms based on discriminative subspace learning. The first algorithm simultaneously learns the discriminative feature subspace and performs clustering. It uses histogram of features in the most discriminative projection...
Understanding how M1 neurons innervate flexible coordinated upper limb reaching and grasping is important for BMI systems that attempt to reproduce the same actions. In this paper, we presented a study for exploring M1 neuronal activities while a non-human primate subject was guided to finish different visual cued spatial reaching and grasping tasks. By applying various configurations of target objects...
AN electroencephalograph (EEG) based computer interface system, also known as brain-computer interface (BCI), offers a new means of computer interaction for those with paralysis or severe neuromuscular disorders. This paper illustrates a novel method using Self Organizing Feature Map (SOFM) to classify left-hand movement imagination, right-hand movement imagination, and word generation from EEG. Welch's...
The popularization of the Internet made it a primary information source for many people. Unfortunately quality of information available on the Internet varies. Therefore, evaluation of credibility of web page content, especially while making important decisions like those concerning health care, medical information, and large purchases, is crucial, but users often lack a necessary knowledge. The main...
Hearing loss has been the most prevalent sensory disability throughout the world. Over 275 million people around the world are affected by various hearing related problems. A conventional hearing screening test's applicability is limited as it requires a feedback response from the subject under test. To overcome such problems, the primary focus of this study is to develop an intelligent hearing ability...
Anomaly detection is one of the major areas of research with the tremendous development of computer networks. Any intrusion detection model designed should have the ability to visualize high dimensional data with high processing and accurate detection rate. Integrated Intrusion detection models combine the advantage of low false positive rate and shorter detection time. Hence this paper proposes an...
This paper introduces a new descriptor for characterizing and classifying the pixels of texture images by means of General Adaptive Neighborhoods (GANs). The GAN of a pixel is a spatial region surrounding it and fitting its local image structure. The features describing each pixel are then regionbased and intensity-based measurements of its corresponding GAN. In addition, these features are combined...
Drum water level is an important parameter for boilers on both thermal power plant and nuclear power plant. It is hard to measure the level correctly. So it brings some difficulties to the control based on the drum water level, even the alarm. Usually, more than three water gauges are installed for drum water level measurement. And it adopts two-out-of-three strategy for obtaining the final alarm...
In this paper, we propose a novel algorithm for Single-hidden Layer Feed forward Neural networks training which is able to exploit information coming from both labeled and unlabeled data for semi-supervised action classification. We extend the Extreme Learning Machine algorithm by incorporating appropriate regularization terms describing geometric properties and discrimination criteria of the training...
A novel concept, uniqueness logic represented via decimal numbers (UL-D), is proposed and defined in this paper. Aiming at achieving the UL-D, we construct a neural network (i.e., NN) based on weights-and-structure-determination algorithm (i.e., the resultant WASD-NN). Differing from the back-propagation neural network (BP-NN) adjusting weights by lengthy iterative process and being unable to acquire...
Coin-tap Test is a kind of NDT methods used commonly. The test is restricted by composite material structure less, but needs a large amount of data. To solve the difficulty of making test pieces and complicated issues of Coin-tap Test data processing, we put forward the clustering analysis of self-organizing neural network to deal with Coin-tap data. With the aid of MATLAB toolbox, the method applied...
The technology underlying brain computer interfaces has recently undergone rapid development, though a variety of issues remain that are currently preventing it from becoming a viable clinical assistive tool. Though decoding of motor output has been shown to be particularly effective when using spikes, these decoders tend to degrade with the loss of subsets of these signals. One potential solution...
Hand orientation is an important control parameter during reach-to-grasp task. In this paper, we presented a study for predicting hand orientation of non-human primate by decoding neural activities from primary motor cortex (M1). A non-human primate subject was guided to do reaching and grasping tasks meanwhile neural activities were acquired by chronically implanted microelectrode arrays. A Support...
We present a novel sampling and processing method for detecting gait events from an insole pressure sensor. Inspired by how tactile data is processed in the brain, we propose the use of timing, instead of intensity, as our event detection feature. By sacrificing the need for accurate intensity measurements, it is possible to achieve superior temporal resolution, which is arguably more important given...
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