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Simulation of IR detector noise is a difficult part in engineering development of 3D dynamic IR scene simulation. A technology of dynamically generating noise of IR detector is provided in this article. First, by computing and analyzing the images sequence of IR detector, the random gauss noise, salt noise and heterogeneity noise is picked up. In scene simulation developed by OSG, a noise "screen"...
Graph-based signal processing (GSP) is an emerging field that is based on representing a dataset using a discrete signal indexed by a graph. Inspired by the recent success of GSP in image processing and signal filtering, in this paper, we demonstrate how GSP can be applied to non-intrusive appliance load monitoring (NALM) due to smoothness of appliance load signatures. NALM refers to disaggregating...
We present a deflation method for Nonnegative Matrix Factorization (NMF) that aims to discover latent components one by one in order of importance. To do so we perform a series of individual decompositions, each of which stands for a deflation step. In each deflation we obtain a dominant component and a nonnegative residual, and then the residual is further used as an input to the next deflation in...
In day to day life, digital mediated interactions and communications being an important constituent. The expeditious growth of electronic communications such as E-mails, micro blogs, SMS and chats etc has fabricated extensively noisy forms of text. It predominantly in young urbanités. The tremendous growth of noises in text are due to a variety of factors, such as the small number of characters allowed...
In this paper, a multi-channel active noise control (ANC) using parametric array loudspeakers (PALs) is proposed to solve the noise problem in a factory. The PAL is a type of directional loudspeaker making use of the nonlinear acoustic effects. There are two advantages when PALs are used as the secondary sources in a multi-channel ANC system. First, noise levels can be reduced at the targeted locations,...
Vehicle localization is the primary information needed for advanced tasks like navigation. This information is usually provided by the use of Global Positioning System (GPS) receivers. However, the low accuracy of GPS in urban environments makes it unreliable for further treatments. The combination of GPS data and additional sensors can improve the localization precision. In this article, a marking...
The RANdom SAmple Consensus (RANSAC) algorithm, as a robust parameter estimator, has been widely used to remove gross errors. However, there is less work on analyzing the uncertainty produced by the RANSAC. This paper fills this gap by presenting an uncertainty estimation algorithm for the RANSAC. Based on a thorough analysis on the uncertainty of the model parameters generated during the random hypothesis...
Image in painting has been a popular study point in recent years and a number of strategies have been developed. Partial differential equation (PDE) image in painting approach often acts as a fundamental building block in this area. However, the high computing load limits the application of PDE-based image in painting, especially in mobile terminal. In this paper, first an enhanced Curvature-Driven...
Human listeners are capable of recognizing speech in noisy environment, while most of the traditional speech recognition methods do not perform well in the presence of noise. Unlike traditional Mel-frequency cepstral coefficient (MFCC)-based method, this study proposes a phoneme classification technique using the neural responses of a physiologically-based computational model of the auditory periphery...
Classification is a supervised learning technique typically uses two-thirds of the given annotated data set for training and the remaining for test. In this paper, we developed a frame work which uses less than one-third of the data set for training and tests the remaining two-thirds of the data and still gives results comparable to other classifiers. To achieve good classification accuracy with small...
Almost every computer vision applications used background subtraction method to detect moving objects from video sequence. Moving object detection and tracking is generally the first step in many applications such as face detection, traffic surveillance, object recognition, detection of unattended bags, people counting etc. Background modeling is very useful and effective method for locating objects...
Wireless multihop networks have a wide variety of applications, due to their rapid deployment times and minimal configuration requirements. Transmissions in wireless networks may require performance guarantees, which can be achieved by using advanced routing strategies. We examine one such performance metric, namely reliability, or packet delivery ratio in a failure-prone wireless network. We use...
Comodulation masking release (CMR) is the effect of enhanced signal detection in the presence of maskers with coherent temporal fluctuations of frequency components. To gain insight into the physiological mechanism of CMR, this study employs a computational model of the auditory nerve to simulate neural responses using a band-widening paradigm at 2 kHz. Signal detection theory was used to relate the...
In this work, we employ a pair wise Markov Random Field (MRF) and a Conditional Random Field (CRF) for bi-level image segmentation and denoising. For both tasks, the Ising pair wise model and the Iterative Conditional Mode (ICM) inference method are implemented, assuming the parameters of the unary and pair wise potentials are known. Experimental results demonstrate the effectiveness of the proposed...
We consider the use of graph cuts technique to efficiently segment the full tissue volume of the entire heart or important parts of it such as ventricles in Magnetic Resonance Imaging (MRI) scans for different species. With the segmented 3-D volume of the heart, simulations of electrical waves propagating through the tissue can be done. The modeled wave results can then be compared directly to the...
Modeling and analysis of low frequency noise in circuit simulators with time-varying bias conditions is a long-standing open problem. In this paper, we offer a definite solution for this problem and present a model for low-frequency noise that captures the internal, stochastic dynamics of the individual noise sources via dedicated internal pseudo nodes that are coupled with the rest of the circuit...
We address the problem of controlling bloat in genetic programming(GP) for image noise reduction. One of the most basic nonlinear filters for image noise reduction is the stack filter, and GP is suitable for estimating the min-max function used for a stack filter. However, bloat often occurs when the min-max function is estimated with GP. In order to enhance image noise reduction with GP, we extend...
We will define two models of error-detecting codes based on quasigroups of arbitrary order. For some special cases of these two models we provide experimental results for the probability of undetected errors if a given quasigroup of order 4 is used for coding. At the end, we will compare the considered special cases.
Within the field of automated video analysis, detection of moving objects remains a challenging task due to the presence of dynamic background and camera motion. Dynamic scenes contain some moving objects such as trees jiggling slightly and water flowing irregularly. In this paper, we present an algorithm to address the problem of dynamic background, which employs spatio-temporal context and background...
The Inverted Pendulum is the benchmark system for control methods. Most linear controllers are not efficient under the situations of disturbances and other uncertainties. As high precision and robustness are required, a sliding mode controller is used in this work. Due to uncertainties, a model free based observer is used to estimate some states. The simulation and real experiment results demonstrate...
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