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In order to improve the deficiency generated from uneven distribution of anchors in the distributed semidefinite programming (SDP) method, improved distributed method is proposed for solving Euclidean metric localization problems that arise from large-scale wireless sensor networks (WSN). By introducing the change of factorization, nonlinear programming (NLP) model is presented on each subarea, and...
Snoring is one of the representative phenomena of the sleep disorder and detection of snoring is quite important for improving quality of daily human life. The purpose of this research is to define the noises of the ordinary sleep situation and to find its characteristics as a preliminary research of snoring detection. Differently from previous snoring researches, we use a built-in sound recording...
A low power, low noise implantable neural recording interface for use in a Radio-Frequency Identification (RFID) is presented in this paper. A two stage neural amplifier and 8 bit Pipelined Analog to Digital Converter (ADC) are integrated in this system. The optimized number of amplifier stages demonstrates the minimum power and area consumption; The ADC utilizes a novel offset cancellation technique...
The extraction of intended kinetic information from an EEG signal can have several applications related to the rehabilitation for subjects with various neurological disorders. However, the task is mainly constrained by the low signal-to-noise ratio for the EEG signals. It is well known that the cortical activity takes place at a very low frequency since it is characterized by the dropping of movement...
A new nonlinearity, instability and non-stationary signal processing method named improved Hilbert-Huang transform was proposed to analyze the measured oscillatory signal from wide area measurement system. Based on this method, the mode mixing of the measured signal in decomposition process was removed and the scheme has advantages of good performance of anti-interference. The measured signal was...
This paper presents an investigation into the Website Boundary Detection (WBD) problem in the dynamic context. In the dynamic context (as opposed to the static context) the web data to be considered is not fully available prior to the start of the website boundary detection process. The dynamic approaches presented in this paper are all probabilistic and based on the concept of random walks, three...
Background subtraction is one of important fundamental steps in many image processing applications such as object recognition, detection, tracking, human behavior analysis in video surveillance systems, etc. So the background subtraction method must be efficiency, that is saving time and space and have a good performance. In order to achieve this aim, a new background subtraction method is proposed...
A new approach to denoise chaotic signals based on ensemble empirical mode decomposition (EEMD) is proposed. The EEMD technique is first used to decompose the noisy chaotic signal into the so-called intrinsic mode functions (IMFs). A criterion is proposed to determine which modes are used to reconstruct the denoised signal. Computer simulations are used to demonstrate the effect of the method. The...
We propose extensions of the classical JSM-method and the Naive Bayesian classifier for the case of triadic relational data. We performed a series of experiments on various types of data (both real and synthetic) to estimate quality of classification techniques and compare them with other classification algorithms that generate hypotheses, e.g. ID3 and Random Forest. In addition to classification...
The traffic noise of developing countries in Southeast Asia were characterized by relatively high noise exposure levels. On the other hand, casement windows are widely used in those countries. However, these windows prove to be impermissible to noise level because the window ventilating slits serve as a direct pathway to allow traffic noise to enter the home. Presented here is a concept for manufacturing...
In clinical medicine fetal electrocardiograms (ECGs) are useful for monitoring fetal health during pregnancy. This research investigates a variety of adaptive filtering techniques to remove maternal interference from fetal ECGs and to determine which techniques are most effective under varying circumstances. Experimental results suggest that a sequential combination of adaptive linear prediction coding...
The time-delay in the teleoperation system is an important parameter affecting the stability and performance. A time delay prediction method based on EMD(Empirical Mode Decomposition) and Elman neural network is proposed in this paper. Firstly, time delay sequence is separated into IMFs by EMD, then the first several IMFs are subtracted from time delay signals as noise. The sum of rest IMFs are taken...
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...
Huge variety of medicine cures diseases. But unlabeled pills sometimes confuse people, even causing adverse drug events. This paper introduces a high accuracy automatic pill recognition method based on pill imprint which is a main discriminative factor between different pills. To describe the imprint information clearly, we propose a Two-step Sampling Distance Sets (TSDS) descriptor based on Distance...
Video tools developed today, teachers can record lecture videos and upload these lecture videos to e-learning system themselves. However, some students may only do not understand some fragments but they have to waste unnecessary time download entire video, and therefore video scene segmentation is relative importance. In addition, in traditional teaching model, students must listen and transcribe...
In this paper, we propose to apply the nonparallel support vector machine (NPSVM) for positive and unlabeled learning problem(PU learning problem) in which only a small positive examples and a large unlabeled examples can be used. Like Biased-SVM, NPSVM treats the unlabeled set as the negative set with noise, while NPSVM is modified so that, the first primal problem is constructed such that all the...
This paper presents a state-space (subspace) method for identification of parallel-cascade joint stiffness from short segments of data. It provides unbiased estimates of stiffness by accounting for the contributions of initial conditions of each segment. The method is important in situations where it is not possible to acquire a long stationary data due to switching or time-varying behavior. The power...
Terrain-aided navigation technology estimates position information based on the terrain elevation data, and corrects the inertial navigation system (INS) error. A terrain matching algorithm based on B-spline neural network and extended Kalman filter (EKF) is proposed for unmanned aerial vehicle (UAV). In order to improve the accuracy of traditional terrain linearization method, B-spline neural network...
As one of the geomagnetic matching positioning methods, Iterative Closest Contour Point (ICCP) has a high requirement on precision of the initial geomagnetic matching position, and it is easy to fall into the local optimum. Considering that inertial navigation system (INS) has a characteristic of high precision location in a short period of time, the position increment between the two adjacent geomagnetic...
Microarray is one of the most promising tools available for researchers in the life sciences to study gene expression profiles. Through microarray analysis, gene expression levels can be obtained, and the biological information of a disease can be identified. The gene expression information embedded in the microarray is extracted using image-processing techniques. Gridding is one of the important...
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