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This paper illustrates the procedure that takes advantage of the properties of discrete wavelet frames so as to improve the learning efficiency of static model representations. The focus is on using orthonormal basis functions due to its convergence properties and compactly supported in frequency domain. The network trained with stochastic gradient type algorithm is presented. Results obtained for...
Electrocardiogram (ECG) signal involves significant information about heart state and is one of the common tools for cardiologist in diagnosis of heart failures. Using adaptive filters for filtering this signal, which inherently has nonstationary features, is used as one of the known methods. In this paper, the wavelet transform and also a neural network (NN) based on adaptive filters are used for...
Travel time prediction is a very important problem in intelligent transportation system research. We examine the use of boosting, a machine learning technique in travel time prediction, and combine boosting and neural network models to increase prediction accuracy. In addition, quality of service (QoS) factors such as bandwidth play an important role in travel time prediction, so we also explore the...
Simulating spiking neural networks is of great interest to scientists wanting to model the functioning of the brain. However, large-scale models are expensive to simulate due to the number and interconnectedness of neurons in the brain. Furthermore, where such simulations are used in an embodied setting, the simulation must be real-time in order to be useful. In this paper we present NeMo, a platform...
Many different types of keystroke dynamics approaches have been explored to protect personal data in networked systems. Keystroke patterns are behavioral biometrics, and are considered to be as unique to an individual as a signature. This paper presents a new approach to keystroke analysis that uses key press interval ratios to authenticate users. Participants in this study registered their passwords...
This paper presents a clutter reduction system when medium-high correlated Weibull-distributed clutter governs the environment of a coherent radar system. This proposal is based on the capabilities of learning of some artificial intelligence techniques, such as the neural networks. This capability of learning of the neural networks is used to learn some statistical characteristics of the radar environment...
Automatic speech recognition (ASR) has made great strides with the development of digital signal processing hardware and software especially using English as the language of choice. In this paper, a new feature extraction method is presented to identify vowels recorded from 80 Malaysian speakers. The features are obtained from Vocal Tract Model based on Bandwidth (BW) approach. The bandwidth is determined...
This paper presents simple methods for translating Kod Tangan Bahasa Melayu (KTBM) into voice signal based on subject head and two hand gestures. Different gesture signs made by different subjects are captured using a USB Web camera in RGB video stream format with a screen bit depth of 24 bits and a resolution of 320 times 240 pixels. The recorded video of the sign language is divided into number...
In this paper, a simple method for crack identification in steel plates based on statistical time energy is presented. A simple experimental procedure is also proposed to measure the vibration at different positions of a steel plate. The plate is excited by an impulse signal and made to vibrate; statistical features are then extracted from the vibration signals which are measured at different locations...
Due to the nature of job, unhealthy social habits and voice abuse, the people are subjected to the risk of voice problems. It is well known that most of vocal fold pathologies cause changes in the acoustic voice signal. Therefore, the voice signal can be a useful tool to diagnose them. Acoustic voice analysis can be used to characterize the pathological voices. This paper presents the detection of...
Traditionally, loudspeaker's quality control has been done manually and inspection of loudspeaker faults is time consuming and causes error in the quality evaluation. In order to reduce the time consumption and errors in the quality evaluation, in this research work, a simple loudspeaker diagnosing system is developed based on the harmonic distortion. The faulty and normal loudspeakers are tested...
In this paper, a simple method for crack identification in steel plates based on frame energy based discrete cosine transformation (DCT) is presented. A simple experimental procedure is also proposed to measure the vibration at different positions of the steel plate. The plate is excited by an impulse signal and made to vibrate. Energy based DCT features are then extracted from the vibration signals...
This paper presents a new neural network (NN) algorithm for real-time retrievals of low amounts of precipitable water vapor (PWV) and integrated liquid water from millimeter-wave ground-based observations. Measurements are collected by the 183.3-GHz G-band vapor radiometer (GVR) operating at the Atmospheric Radiation Measurement (ARM) Program Climate Research Facility, Barrow, AK. The NN provides...
Traditionally, loudspeaker's quality control has been done manually and inspection of loudspeaker faults is time consuming and causes error in the quality evaluation. In order to reduce the time consumption and errors in the quality evaluation, in this research work, a simple loudspeaker diagnosing system is developed based on the harmonic distortion. The faulty and normal loudspeakers are tested...
In this paper we investigate the use of brain signatures as a possible biometric authentication technique. Research on brain EEG signals has shown that individuals exhibit unique brain patterns for similar tasks. In this paper we use brain EEG signals recorded during the performance of three mental tasks to identify six individuals. PSD features using Welch algorithm is extracted from the EEG Beta...
The computation of a mobile robot position and orientation is a common task in the area of computer vision and image processing. For a successful application, it is important that the position and orientation of a mobile robot must be determined properly. In this paper, a simple procedure for determining the orientation of a mobile robot using two cameras is presented. The two cameras are used to...
Motor imagery is the mental simulation of a motor act that includes preparation for movement and mental operations of motor representations implicitly or explicitly. The ability of an individual to control his EEG through imaginary mental tasks enables him to control devices through a brain machine interfaces (BMI). In other words a BMI can be used to rehabilitate people suffering from neuromuscular...
Monitoring systems for motorbike industry requires high and efficient degree of performance. In recent years, automatic identification and diagnosis of motorbike engine faults has become a very complex and critical task. The noise produced by a motorbike engine is an important information source of fault diagnosis. Artificial Neural Network finds applications in many industries including condition...
Sign language is the primary communication method that impaired hearing people used in their daily life. Sign language recognition has gained a lot of attention recently by researchers in computer vision. Sign language recognition systems in general require the knowledge of the hand's position, shape, motion, orientation and facial expression. In this paper we present a simple method for converting...
The purpose of this paper is to present the development of a system capable of detecting incipient malfunction and also verify the correct operation of opening and closing of high voltage switches thru digital analysis of the torque curve supplied by the drive engine during the maneuvers of the switch, surpassing the difficulties involved with the direct monitoring of the contacts. This system will...
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