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In this paper we propose a technique to determine the decision thresholds in multi-bit distributed detection. Detection thresholds are required to quantize the acquired information from the environment to send them to a fusion center. In multi-bit detection, decision making is complicated and in most cases, methods based on simulation or Person by Person Optimizations are applied to find the thresholds...
This paper introduces a proper quality test of RZ modulated digital signal from non-coherent recovery process in ultra wide-band (UWB) transceiver which is designed by system-in-package (SiP) technology for wireless mobile application. 3-dimensional (3D) BER with a marginal window which is multiple sampling points set in eye-diagram is proposed. An area of 3D BER opening at specific BER level provides...
This article presents an instrumental variable method dedicated to non-linear Hammerstein systems operating in closed loop. The linear process is a Box-Jenkins model and the non-linear part is a sum of known basis functions. The performance of the proposed algorithm is illustrated by a numerical example.
This paper presents a novel deterministic approach for the identification of linear continuous-time systems. The approach is based on the projection of measured signals onto the finite dimensional signal subspace whose basis is determined by the parameter structure of the target system model. In this paper, we describe the basic concept and implementation of the proposed identification framework,...
The stochastic distribution control (SDC) problem is a generalised form of the minimum variance control problem where non-Gaussian noise distributions are encountered. The problem has been previously solved using two alternative approaches. When it is assumed that the output probability distribution function (PDF) is measurable, then a parameterized controller is obtained. If on the other hand this...
This paper addresses a state-estimation problem for nonlinear systems with non-Gaussian noise and interval constraints on the state vector. We propose new efficient algorithms, which are based on unscented Kalman filter (UKF) and ensemble Kalman filter (EnKF). We use truncated UKF (TUKF) in Gaussian sum filter (GSF) framework, which is named constrained unscented GSF (CUGSF). And we proposed an efficient...
This paper presents a discrete wavelet transform (DWT) domain watermark detection approach using Gaussian mixture model (GMM) with automated model selection. More specifically, instead of using traditional expectation maximization (EM) algorithm for parameter estimation in mixture model, where the number of model components need to be fixed in advance, the proposed approach employs the component-wise...
In weighted mean squares error (WMSE) function, each sample error multiplies a weighting coefficient, then it can make noise error have a smaller proportion in the cost function, even the outliers can't affect the learning of the neural networks by tuning the smooth parameter , which enhances the anti-noise ability of neural networks. If the samples don't have noise samples, weighted mean squares...
The problem of the detection of a signal in the presence of broad-band noise and interferences that lie in a subspace that is imperfectly known is considered. It is assumed that a basis (or generating set) of the interference subspace is known up to additive white Gaussian noise. This amounts to assuming that each of these basis vectors lies in a cone, the aperture of which depends upon the level...
This paper describes and analyzes population size management, which can be used to enhance the efficiency of the extended compact genetic algorithm (ECGA). The ECGA is a selectorecombinative algorithm that requires an adequate sampling to generate a high-quality model of the problem. Population size management decreases the overall running time of the optimization process by splitting the algorithm...
This paper proposes the concept of inverse perlin noise which is a reverse process of perlin noise. The proposed method enables users to feel the haptic sensation when he/she rubs on the surface of an object. We extract individual random signals from a target object modeled by perlin noise and apply them to haptic actuators. In order to evaluate the proposed method, we compute errors between the original...
Scanning probes can be used for storage of data at ultra-high areal densities, beyond those achieved by other techniques. Thermo-mechanical probe storage is one variant of scanning-probe technology in which data is stored in the form of indentations in thin polymer films. A simplified channel model of thermo-mechanical probe storage is first introduced, derived from a comprehensive characterization...
The problem of efficient video transmission over noisy channels involves high compression rates and robustness to channel errors. In the framework of multiple description coding (MDC), we focus on the direct estimation of the source from two noisy descriptions, without trying to estimate the single descriptions. The challenge is to reconstruct a central signal with distortion as small as possible...
This paper describes a noise-aware dominance operator for evolutionary algorithms to solve the multiobjective optimization problems (MOPs) that contain noise in their objective functions. This operator takes objective value samples of given two individuals (or solution candidates), estimates the impacts of noise on the samples and determines whether it is confident enough to judge which one is superior/inferior...
Sensing-through-wall will benefit various applications such as emergence rescues and military operations. In order to add more signal processing functionality, it is vital to understand the characterization of sense-through-wall channel. In this paper, we propose a statistical channel model on a basis of real experimental data using UWB noise radar. We employ CLEAN algorithm to obtain the multipath...
A novel adaptive nonlinear controller is presented for nonlinear active noise control systems, which is expanded by memory function mapping on the basis of a single neuron structure, and a generalized filtered-X gradient descent algorithm is developed to attenuate the nonlinear, non-Gaussian noises, which defines the weighted sum of Renyi's quadratic error entropy and the mean square error as the...
In this paper, we propose image enhancement of microarray images using histogram specification method. The proposed approach consists of system model that discuss about finding the type of noise present in the image and enhancing image by removing the noise present in the image. The proposed method is very efficient as it enhances image by revealing most of the microarray spots which is used for subsequent...
During the investigation and evaluation of movement, we are interested in the filter and in smoothing the state of measurement at the previous times, called smoother RTS (Rauch-Tung-Striebel), in order to have a smooth orbit of the movement. Moving objects require an essential time period to speed up to achieve the necessary speed. Thus the obtained measurement and predicted values cannot be beyond...
This paper gathers some of the authors' work with the family of the elliptically contoured distributions and its application to the analysis of performance in communication systems. Specifically, the Pearson type VII distribution is used to derive a closed-form expression for the BER in an LTE uplink system over a Rayleigh fading channel. ECDs possess many nice properties similar to those of multivariate...
Although there are some recent characterizations of Multivariate Gauss Markov-Random Field (MGMRF) models, these are limited to cases where the interaction matrix coefficients are modeled with some special form. We extend the modeling and parameter estimation for the interaction matrix coefficients for a general anisotropic MGMRF. Although the MGMRF is a natural generalization of its univariate counterpart,...
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