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This paper presents a new direction recognition algorithm of moving targets using an impulse radio ultra-wideband (IR-UWB) radar system. To improve the stability of the direction recognition of moving targets, the algorithm divides the whole observation area into three main areas. Each main area consists of three sub-areas. Moreover, we use the mid-point of the effective area as the position of the...
Mobile wearable sensors have demonstrated great potential in a broad range of applications in healthcare and wellness. These technologies are known for their potential to revolutionize the way next generation medical services are supplied and consumed by providing more effective interventions, improving health outcomes, and substantially reducing healthcare costs. Despite these potentials, utilization...
This paper addresses compressive sensing for multi-channel ECG. Compared to the traditional sparse signal recovery approach which decomposes the signal into the product of a dictionary and a sparse vector, the recently developed cosparse approach exploits sparsity of the product of an analysis matrix and the original signal. We apply the cosparse Greedy Analysis Pursuit (GAP) algorithm for compressive...
In applying mental imagery brain-computer interfaces (BCIs) to end users, training is a key part for novice users to get control. In general learning situations, it is an established concept that a trainer assists a trainee to improve his/her aptitude in certain skills. In this work, we want to evaluate whether we can apply this concept in the context of event-related desynchronization (ERD) based,...
Long-term recording of Electrocardiogram (ECG) signals plays an important role in health care systems for diagnostic and treatment purposes of heart diseases. Clustering and classification of collecting data are essential parts for detecting concealed information of P-QRS-T waves in the long-term ECG recording. Currently used algorithms do have their share of drawbacks: 1) clustering and classification...
In this paper we focus on radio-based navigation of an autonomous dynamic swarm system of agents. We assess the anchor-free localization and investigate the impact of the performance of localization to a swarm flocking algorithm. Low latency is crucial in a dynamic autonomous swarm system to control the formation of the swarm. Therefore, an agent applies the randomized orthogonal frequency-division...
In this paper, a modified K-means algorithm is proposed to categorize a set of data. K-means algorithm is a simple and easy clustering method which can efficiently classify a large number of continuous numerical data of high-dimensions. Moreover, the data in each cluster are similar to one another. However, it is vulnerable to outliers and noisy data, and it spends much executive time in classifying...
This paper presents a novel full-image guided filtering based on eight-connected weight propagation for dense stereo matching. The proposed method has three main features: first, the proposed eight-connected weight propagation is more approximate compared to previous approach, second, the pixels employed into the filtering are all the pixels without constrained by one fixed window, last but not least,...
Since the view of hiding information in MV will increase the bit rate greatly, this paper proposes a new MV based video hiding algorithm, which embeds the data during the motion estimation course and selects the MV with minimizing cost as the current macroblock block's MV. Experiment shows that, under the same degree of SNR, this algorithm can restrict the compressed video's increase introduced by...
The intelligent transportation system has demonstrated its strong advantages in solving the urban transport problem. One of its important roles is able to reflect the traffic conditions timely through the floating car. The key problem is to find out the candidate road sections from the vast road network quickly. Then we make the floating car match to the corresponding road by the map-matching algorithm...
The change-point detection theory is used to identify abrupt changes in the network traffic. The literature has focused on longitudinal traffic analysis, namely, detecting sudden peak changes, rather than analyzing the traffic pattern on a 24h typical day. As traffic varies throughout the day, it is essential to consider the concrete traffic period in which the anomaly occurs, which is useful for...
In this paper the recent results of Synthetic Aperture Radar (SAR) experiments conducted at the Warsaw University of Technology are presented. In the experiments an SAR radar was mounted on a lightweight airborne platform. The main goal of this experiment was to verify the possibility of obtaining high quality SAR image using navigation data from a low-cost Inertial Navigation System (INS) and classical...
A new optimization algorithm, namely the Forest Algorithm (FA), is introduced for the first time. This algorithm simulates trees' growth, reproduction and death in a forest to perform optimization. In the algorithm, trees and branches represent a collection of trial solutions and parameters needed to be optimized respectively, and three mechanisms, i.e. Growth, proliferation and death, are employed...
The matrix completion problem addresses the recovery of a low-rank matrix from a subset of its entries. In this paper, we analyze rank-r matrix completion algorithm based on the rank-r singular value decomposition (SVD). We introduce the doubly-restricted contraction constant (DRCC), a characteristic of a matrix, which predicts the feasibility of matrix recovery from a subset of its entries. We establish...
For the feature extraction of motor imaginary EEG (electroencephalography) in the study of brain-computer interface(BCI), a method of extracting EEG features based on wavelet package combined with ICA (Independent component analysis) was adopted to extract the signals produced by imaginary movement, event related desynchronization or event related synchronization (ERD/ERS). First, in order to eliminate...
This paper proposes an incremental localization algorithm in wireless sensor network based on the estimation of distribution algorithms. In this algorithm, the distances between an unknown node and the anchor nodes are measured, and then samples are chosen in the area in which the unknown node is located possibly. Thus, the high accuracy samples selection is based on the calculated fitness, and the...
Finding roots of words is widely used in document classification and text mining. Computational methods of text similarity are intensely utilized on the English words and successful outcomes are obtained. On the other hand, applying the aforementioned methods on the Turkish words did not give the similar success. In this study, a novel similarity computation algorithm is developed. By using this algorithm...
In this study, we have classified well known 20 News Group Set that contains 20.000 documents with a Naïve Bayes Classifier. Rather than using traditional Naïve Bayes method, we have used logarithm based classifier that is more suitable for information retrieval tasks. We successfully evaluated the performance of our implementation using two other classification studies (Icsiboost-bigram and EM) on...
We present a novel parallelized formulation for fast non-linear image registration. By carefully analyzing the mathematical structure of the intensity independent Normalized Gradient Fields distance measure, we obtain a scalable, parallel algorithm that combines fast registration and high accuracy to an attractive package. Based on an initial formulation as an optimization problem, we derive a per...
Localization algorithm is an important and challenging topic in today's wireless sensor networks (WSNs). In order to improve the localization accuracy, a weighted centroid localization algorithm based on least square to predict the location of any sensor in a WSNs is proposed in this paper. The proposed algorithm proposes a Least-Square-based weight model which can reasonably weigh the proportion...
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