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Dual-tone multi-frequency (DTMF) is a signaling standard in telecom applications that produces two tones simultaneously for each key press. The DTMF tones are chosen such that decoding the pressed key from the received tones is very easier. The DTMF tone detection is very crucial block in several telecom based embedded systems. As the current generation embedded systems are looking for key feature...
The emergence of data-intensive problems in areas like computational biology, astronomy, medical imaging, etc. has emphasized the need for fast and efficient very large Fourier Transforms. Recent work has shown that we can compute million-point transforms efficiently provided the data is sparse in the frequency domain. Processing input samples at rates approaching 1 GHz would allow real-time processing...
This paper concerns active control of impulsive noise. Due to nature of impulsive noise, it is very hard to be reduced with classical noise control algorithms. They used to diverge after suddenly receiving high signal values. Several algorithms have been proposed for this purpose, which are usually modifications of the popular FXLMS algorithm. In this paper an algorithm based on FXLMS, but incorporating...
A video surveillance system is primarily designed to track key objects, or people exhibiting suspicious behavior, as they move from one position to another and record it for possible future use. The critical parts of an object tracking algorithm are object segmentation, image clusters detection, and identification and tracking of these image clusters. The major roadblocks of the tracking algorithm...
With the progress in VLSI technology increase in circuit density is obvious. In present integrated circuits, electrical power is distributed to the large number of components of the chip over a network of on chip conductors. The systematic arrangement of the power distribution network (PDN) is commonly termed as power grid. The challenge of efficient PDN design escalates to a greater extent especially...
Learning motion control as a unified process of designing the reference trajectory and the controller is one of the most challenging problems in robotics. The complexity of the problem prevents most of the existing optimization algorithms from giving satisfactory results. While model-based algorithms like iterative linear-quadratic-Gaussian (iLQG) can be used to design a suitable controller for the...
Clustering algorithms based on Grid are attractive for the task of data partition in spatial database. In the background of big data more and more research focuses on how to solve the conflict between efficiency and accuracy of clustering. Existing Grid-based clustering algorithms generally have a high time efficiency without considering the distribution of the data inside a grid. In this paper, a...
The paper presents a computational procedure of a multichannel Fast Affine Projection algorithm. The procedure also includes Sliding Window linear prediction, Gradient Adaptive Step-Size and fast computation of adaptive filter output signal. An example of the algorithm application in a combined Feed-Forward and Feed Backward Active Noise Control system, which can be viewed as a two-channel adaptive...
Loud Computing is emerging as a major trend in ICT industry. However, as with any new technology it raises new major challenges and one of them concerns the resource provisioning. Indeed, modern Cloud applications deal with a dynamic context and have to constantly adapt themselves in order to meet Quality of Service (QoS) requirements. This situation calls for advanced solutions designed to dynamically...
RNA-seq enables quantification of the human transcriptome. Estimation of gene expression is a fundamental issue in the analysis of RNA-seq data. However, there is an inherent ambiguity in distinguishing between genes with very low expression and experimental or transcriptional noise. We conducted an exploratory investigation of some factors that may affect gene expression calls. We observed that the...
Arterial blood pressure (ABP) is an important vital sign of the cardiovascular system. As with other physiological signals, its measurement can be corrupted by different sources of noise, interference, and artifact. Here, we present an algorithm for the quantification of signal quality and for the reconstruction of the ABP waveform in noise-corrupted segments of the measurement. The algorithm quantifies...
The problem of efficient hardware implementation of a reliable spectrum sensing method is crucial for the practical realization of the cognitive radio terminal. This paper analyses the influence of various hardware implementation issues on the performance of the sequential energy-detection-based spectrum sensing algorithm. In particular, the necessity of noise inclusion in noise variance estimation...
Coronary Wave Intensity Analysis (cWIA) is a technique capable of separating the effects of proximal arterial haemodynamics from cardiac mechanics. The cWIA ability to establish a mechanistic link between coronary haemodynamics measurements and the underlying pathophysiology has been widely demonstrated. Moreover, the prognostic value of a cWIA-derived metric has been recently proved. However, the...
Video leaking signal detection is an important part of TEMPEST, which is the technologies research focus on the investigations and studies of compromising emanations. A novel video leaking signal detection algorithm based on spectral centroid has been developed. Using the property that spectral centroid can accurately identify the signal energy center in frequency domain, the proposed algorithm can...
The research on community structure is a key to analyze the network functionality and topology, and thus it is significant to detect and analysis the community structure. During the abstract process from an actual system to a network, especially for a large-scale network, it is inevitable to have mistaken connections between nodes or have connection missing. In addition, in real applications, from...
Dimensionality reduction as a preprocessing step to machine learning is effective in removing irrelevant and redundant data, increasing learning accuracy, and improving result comprehensibility. However, the recent increase of dimensionality of data poses a severe challenge to many existing feature selection and feature extraction methods with respect to efficiency and effectiveness. In the field...
Maximum common sub-graph isomorphism (MCS) is a famous NP-hard problem in graph processing. The problem has found application in many areas where the similarity of graphs is important, for example in scene matching, video indexing, chemical similarity and shape analysis. In this paper, a novel algorithm Qwalk is proposed for approximate MCS, utilizing the discrete-time quantum walk. Based on the new...
The Electroencephalogram signal which is picked up by electrodes from the skull of the patient's body is effected severely by noise of power line, noise of human body muscles, noise of human lungs and noise of the baseline. The baseline noises arise even because of patients body movements and breathing, the sensors are loosely connected and eye movements. Researchers have applied many algorithms for...
DBSCAN is a clustering algorithm based on density. It can divide regions which have a high density for clusters, shield the noise effectively and discover clusters of arbitrary shape and any size from dataset. However, DBSCAN algorithm needs to traverse dataset to find core objects, so it results in large amount of I/O cost when processing large-scale datasets. A fast algorithm (BEDBSCAN) is developed...
Background subtraction is a popular technique used in accurate foreground extraction with a stationary background. Since most outdoor surveillance videos are taken in complex environments, their "stationary" backgrounds change in some unknown patterns, which make the perfect foreground extraction very difficult. Based on visual background extractor (ViBe) scheme, in this paper we propose...
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