The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
This paper forms a part of a series of recent studies we have undertaken, where the problem of nonlinear signal modelling is examined. We assume that an observed "output" signal is derived from a Volterra filter that is driven by a Gaussian input. Both the filter parameters and the input signal are unknown and therefore the problem can be classified as blind or unsupervised in nature. In...
When a Kalman filter is applied to an image for restoration purposes, the model of the original image affects the accuracy of the restoration. The model for effective restoration depends on the correlation of the original image and the variance of the noise. If these parameters are unknown, they have to be estimated from the observed image. In this paper, a method to estimate the unknown parameters...
Conceptual modelling is a mature management approach, likes supply chain management within virtual enterprises. This approach is confronted with the challenge to transform from a current centralized approach towards an open and collaborative approach. This paper elaborates on the challenge to enable the collaborative editing of certain modelling information. This decentralised decision making process...
The adaptive filter is an important workhorse of digital signal processing having a vast variety of applications in almost every branch of modern electronics. Today there is an abundance of algorithms with different performance and computational characteristics. In this paper we address the class of delayless subband adaptive filters (SAF). Although this class of adaptive filters have been popular...
Multi-label classification (MLC) is a type of structured output prediction problems where a given instance can be associated to more than one labels at a time. From the probabilistic point of view, a model predicts a set of labels y given an input vector v by learning a conditional distribution p(y|v). This paper presents a powerful model called a Neural Conditional Energy Model (NCEM) to solve MLC...
The limitation with the method of calculating surface water velocity is the direct contact of the velocity measurement tool to the flowing water which results in the mechanical wear and high maintenance cost. This paper describes the flow visualization and surface water velocity measurement technique using the non-intrusive method. This system gives the instantaneous results and is reliable, flexible...
This paper addresses the problem of designing closed-loop control of emotion based on affective measures and computing. The work is focused on design rule base control system that serves for positive emotion state stabilization. The proposed approach is based on analyzing of breathing signal. The measured signal is analyzed according to features important for emotional changes. Knowing emotional state...
Anomaly detection has been a hot topic in recent years due to its capability of detecting zero attacks. In this paper, we propose a new on-line anomaly detection method based on LMS algorithm. The basic idea of the LMS-based detector is to predict IGTE using IGFE, given the high linear correlation between them. Using the artificial synthetic data, it is shown that the LMS-based detector possesses...
Thalamus is a very important part of the human brain. It has been reported to act as a relay for the messaging taking place between the cortical and sub-cortical regions of the brain. In the present study, we analyze the functional network between both hemispheres of the brain with the focus on thalamus. We used conditional Granger causality (CGC) and time-resolved partial directed coherence (tPDC)...
We represent a new model of knowledge creation and knowledge utilization. Recently, the one of the important knowledge management issues is how to create knowledge and how to utilize their knowledge. Actually, we cannot maximize the accumulated know-how on various fields, although there are various and a massive of data on the World Wide Web. It is important to consider how to organize knowledge and...
This paper proposes two methods for solving the expert finding problem. In order to enhance the correctness, a C-value method is applied to these methods for query expansion. After query expansion, proposed system calculates correlation between all query terms and experts, and finally outputs a list of experts. The experiment results show that the proposed methods can provide higher precision than...
Asset prices fluctuate up and down chaotically. Traders, investors and fund managers comb the chaos for exploitable patterns with methods such as moving averages from the realm of technical analysis. In this paper we focus on linear moving averages which aim to smooth asset prices removing fluctuations. First, we will develop a method to measure the smoothness for a linear filter. We will also discuss...
Processing bug reports plays an important role for software maintenance. Recently, the issue of detecting duplicate bug reports has been noticed due to their considerable appearances. In the past, many NLP-based detection schemes have been proposed. However, the cluster-level correlation relationships are not extensively considered in the past studies. In this paper, we present an improved detection...
A method is proposed to detect if there is no coupling between an input and an output in open-loop systems. The proposed technique is applicable to MIMO systems, i.e., the intent is to detect models in a transfer matrix. Traditional approaches to input/output (IO) selection are usually performed after the plant model is identified. The proposed approach is applied during the pre-identification stage...
Electroencephalography (EEG) recording are generally corrupted by eye blink artifacts. In this research work, blind source separation (BSS) based methods for removal of eye blink artifacts are presented. Two techniques, namely the Independent Component Analysis (ICA) and the Canonical Correlation Analysis (CCA) are investigated. The efficiency and performance of the BSS methods were compared between...
Error Concealment (EC) algorithms have provided a very useful tool for concealing the errors in digital video streams. The importance of EC methods arises specially in broadcasting and multicasting communications where retransmission of corrupted video sequence is not possible. In this paper, a Motion Vector (MV) space is proposed around each erroneous macroblock (MB) and thus the candidate MV can...
Collecting data continuously in Wireless Sensor Networks (WSNs) with limited power and bandwidth is still a challenging issue. Recently, the sparse nature of these data motivated the use of Compressive Sensing (CS) as an efficient data gathering technique. In this paper, several algorithms are proposed to effectively exploit the temporal correlation and the sparsity inherent in sensor network data...
This paper proposes an online framework to dynamically model the impulse-response function (IRF) of a system having shared-band noises, to facilitate the output prediction in real-time. The online independent-component analysis is performed to un-mix the measured signal. The automatic recognition of the anticipated IRF, amongst the unmixed signals, is achieved by proposing a peak-detection-&-correlation...
Temporal in loop filters present one possible way to reduce noise introduced in compressed video sequences at low bit rates. Some of these filtering approaches make use of the quantized and generally noisy motion information conveyed in the bit stream generated by the encoder. One key feature of such filters is an adaptive filter length depending on the image content and the quality of the motion...
This paper aims at establishing the cumulative distribution function (CDF) of the output variable of the probabilistic optimal power flow. In the context of the probability weighted moment (PWM), the uncertainties in the power system are modelled by a ninth-order polynomial normal transformation (NPNT) technique, whereby the dependencies among the inputs are conveniently handled. The quasi-Monte Carlo...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.