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检索条件"主题词=Filtering algorithms"

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Maternal ECG elimination and foetal ECG detection-comparison of several algorithms

Maternal ECG elimination and foetal ECG detection-comparison...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： A. Kam A. Cohen Signal Processing Laboratory Department of Electrical and Computer Engineering Ben-Gurion University of the Negev Beersheba Israel

When trying to record a foetal ECG (FECG), one of the main problems is the interference from the maternal ECG (MECG). Three algorithms for eliminating maternal ECG are compared. Two adaptive filtering techniques, LMS (least mean square) and RLS (recursive least squares), are compared to a new algorithm that uses the blind source separation (BSS) theorem to separate the FECG from signals that are recorded with a lot of MECG interference. Simulation studies were first performed. Two independent ECG signals (sources) were simulated; one was considered as the MECG while the other was the FECG. By mixing the two sources with various channels, the algorithms were checked and compared. The algorithms were tested on real data as well as that taken from DAISY (the DAtabase for the Identification of SYstems). Conclusions concerning the mixing system were drawn both from the real data and from the simulation experiments.

关键词： Electrocardiography Interference Adaptive filters Least squares approximation Resonance light scattering Least squares methods filtering algorithms Blind source separation Source separation System testing

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Statistical analysis of the deficient length affine projection adaptive algorithm

Statistical analysis of the deficient length affine projecti...

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European Signal Processing Conference (EUSIPCO)

作者： Sérgio J. M. de Almeida Márcio H. Costa José C. M. Bermudez Escola de Engenharia e Arquitetura Universidade Católica de Pelotas Pelotas-RS Brazil Departamento de Engenharia Elétrica Cidade Universitária Florianópolis-SC Brazil

This paper presents a statistical analysis of the Affine Projection (AP) adaptive algorithm for the insufficient order case. Deterministic recursive equations are derived for the mean weight and mean-square error behavior. The analysis assumes a large number of adaptive coefficients when compared to the algorithm's order, autoregressive input signals and unity step-size. Monte Carlo simulations show excellent agreement with the theoretically predicted behavior. It is shown that the AP coefficients converge in the mean to the initial plant coefficients, producing an unbiased solution even for the correlated input signal case. It is also shown that the steady-state mean square error has a term that is proportional to the power of the unpredictable part of the input signal filtered by the un-modeled part of the unknown impulse response.

关键词： Signal processing algorithms Adaptive filters Least squares approximations Algorithm design and analysis Mathematical model filtering algorithms Steady-state

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Adaptive unscented particle filter based on predicted residual

Adaptive unscented particle filter based on predicted residu...

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IEEE Joint International Information Technology and Artificial Intelligence Conference (ITAIC)

作者： Hua-jian Wang Zhan-rong Jing School of Electronics and Information Engineering Northwestern Polytechnical University Xi'an Shanxi China

In order overcome the particle degradation and non-adjusted online in the traditional particle filter algorithm, an adaptive un scented particle filter algorithm based on predicted residual is proposed. The algorithm adopts a new proposal distribution combing the unscented kalman filter with the adaptive factor. The algorithm uses Unscented Kalman filter to generate a proposal distribution, in which the covariance of the predicted measurement, the cross-covariance of the state and measurement and the covariance of the state update are online adjusted by predicted residual as adaptive factor. Simulation experiments results of nonlinear state estimation demonstrate that the adaptive unscented particle filter is more adaptive and accuracy is also improved.

关键词： Particle filters Particle measurements Atmospheric measurements Prediction algorithms Proposals filtering algorithms Adaptation models

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Performance Analysis of Different Convolution algorithms in GPU Environment

Performance Analysis of Different Convolution Algorithms in ...

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International Conference on Networking, Architecture, and Storage (NAS)

作者： Rui Xu Sheng Ma Yang Guo National University of Defense Technology College of Computer Science Hunan China

ISBN: (纸本)9781538683682

Convolutional neural networks (CNNs) have a wide range of applications in image and video recognition, recommender systems and natural language processing. But CNNs are computationally intensive, and its computational cost is hard to accept. In order to speed up the calculations, people focus on optimizing convolution that account for most of the proportion of CNNs' operation. So, many algorithms have been proposed to accelerate the operation of convolution layers. However, each algorithm has its advantages and disadvantages, and there is no one algorithm that can handle all situations. In this paper, we examine the performance of various algorithms in GPU environment. By building a customized CNN model, we have fully explored the impact of the neural structure on the performance of algorithms, including inference/training speed, memory consumption and power consumption. In addition to the algorithms, we also focus on how their implementations in GPU environment affect their performance. We trace the kernel functions of these implementations to further generalize the characteristics of these algorithms. Finally, we summarize the characteristics of each algorithm., and design a strategy to assigns the appropriate implementation for different convolutional layers in CNNs. With our strategy, we can make AlexNet run 1.2× to 2.8× faster than other strategies in GPU environment. This work has very important meaning for understanding these algorithms and may provide insights for further optimizations of the architecture of GPUs and accelerators.

关键词： Convolution Graphics processing units Feature extraction filtering algorithms Inference algorithms Kernel Convolutional neural networks

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Robust initial alignment algorithm for platform inertial navigation system on disturbance base

Robust initial alignment algorithm for platform inertial nav...

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IEEE Workshop on Advanced Research and Technology in Industry Applications (WARTIA)

作者： Zhibin Guo Yuegang Wang Bin Shan Wuxing Huang Section 304 Xi'an Research Inst. of High-Tech. China

Focus on the initial alignment problem of vehicular platform inertial navigation system(INS) on disturbance base, the main disturbance sources include the Strong Flurry Interference, the engine working, the stuff's movement and the doors' opening and closing were analyzed and the vibration disturbance made from these sources influenced the initial alignment for vehicular platform INS seriously. This kind of vibration disturbance was too complex to establish the model, an H ∞ filter was designed for the platform INS alignment which deemed the vibration disturbance as the indeterminate interference. The simulation results showed that the initial alignment could be accomplished by using this robust Algorithm and the accuracy was within 3'.

关键词： Vibrations Mathematical model filtering algorithms Robustness Equations Noise measurement Vehicles

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Gradient-based adaptive algorithm for minimum phase-all pass decomposition of an FIR system

Gradient-based adaptive algorithm for minimum phase-all pass...

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European Conference on Circuit Theory and Design, ECCTD

作者： M. Flanagan A.D. Fagan Department of Electronic and Electrical Engineering University College Dublin Ireland

An adaptive filtering algorithm which performs minimum phase-all pass (MP-AP) decomposition of an FIR system is proposed. The minimum phase component of the system is modeled as a lattice filter cascaded with a gain stage. Simulation results on randomly generated FIR systems demonstrate convergence of the algorithm to the correct MP-AP decomposition in 92.6% of cases. The algorithm has the additional advantage that it is capable of detecting misconvergence during or after adaptation. These properties combined make the algorithm a strong candidate for use with compound precoding, a pre-equalization method for high-speed modems.

关键词： Adaptive algorithm Finite impulse response filter Lattices Adaptive filters Reflection filtering algorithms Convergence Transversal filters Stochastic processes Modems

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Matrix Operation and Its Application in Computer Engineering

Matrix Operation and Its Application in Computer Engineering

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International Conference on Computer and Information Science (ACIS)

作者： Fang Dong Yinmei Lv Beijing Eightieth Middle School Beijing China

Mathematics is fundamental to natural science. Its content is extensive and profound, and the matrix is an important part of mathematics. It can be seen in many fields. For example, in game theory and economics, the payoff matrix is used to represent the payoff of two game objects in various decision modes. Early cryptographic techniques, such as the Hill code, also used matrix. In the field of chemistry, where quantum theory is used to discuss molecular bonds and spectra, the matrix is applied. In physics, matrices have applications in electronics, mechanics, optics and quantum physics. In the field of computer engineering, it is more widely used, such as computer image processing, 3D animation production, text mining and its' inverted index technology. Therefore, this paper mainly focuses on matrix operations and its application in personalized recommendation methods. This paper adopts recommendation method based on bipartite graph. This method improves the accuracy of recommendation effectively. The experimental results verify its feasibility.

关键词： Bipartite graph Collaboration Internet filtering algorithms Search engines

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Equivariant Filter Design for Discrete-time Systems

Equivariant Filter Design for Discrete-time Systems

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IEEE Conference on Decision and Control

作者： Yixiao Ge Pieter van Goor Robert Mahony Systems Theory and Robotics Group School of Engineering Australian National University Australia

ISBN: (数字)9781665467612

ISBN: (纸本)9781665467629

The kinematics of many nonlinear control systems, especially in the robotics field, admit a transitive Lie-group symmetry, which is useful in high performance observer design. The recently proposed equivariant filter (EqF) exploits equivariance to generate high performance filters for a wide range of real-world systems. However, existing work on the equivariant filter, and equivariance of control systems in general, is based on a continuous-time formulation. In this paper, we first present the equivariant structure of a discrete-time system. We then use this to propose a discrete-time version of the equivariant filter. A novelty of the approach is that the geometry of the symmetry group naturally appears as parallel transport in the reset step of the filter. Preliminary results for linear second order kinematics with separate bearing and range measurements indicate that the discrete EqF significantly outperforms both a discretized version of the continuous EqF and a classical discrete EKF.

关键词： Discrete-time systems Geometry Design methodology Kinematics filtering algorithms Observers Nonlinear control systems

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A time-varying model for DNA sequencing data

A time-varying model for DNA sequencing data

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IEEE/SP Workshop on Statistical Signal Processing (SSP)

作者： N.M. Haan S.J. Godsill Signal Processing Group Department of Engineering University of Cambridge UK

Methods for determining the letters of our genetic code, known as DNA sequencing, currently depend on clever use of electrophoresis to generate data sets indicative of the underlying sequence. Typically the subsequent off-line data processing is carried out using a combination of heuristic methods with little mathematical rigour. We present a novel model which is able to accurately predict the effect of the many biological processes which are involved, and moreover, which is usable on-line. Off-line methods have been hampered by the need for processing in as little time as possible after the data is generated; performing the processing on-line has enabled a more advanced algorithm to be used with associated improved performance. The algorithm is framed within a Bayesian probabilistic framework, thereby allowing representation of the random nature of the generative process, and relies on new advances in the burgeoning field of sequential Monte Carlo methods to perform non-linear filtering and model selection operations.

关键词： DNA Genetics Electrokinetics Sequences Data processing Biological system modeling Predictive models Biological processes filtering algorithms Bayesian methods

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Optimization of linear phase FIR band pass filter using Particle Swarm Optimization with Constriction Factor and Inertia Weight Approach

Optimization of linear phase FIR band pass filter using Part...

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IEEE Symposium on Industrial Electronics & Applications (ISIEA)

作者： Rajib Kar Durbadal Mandal Soumi Bardhan S. P. Ghoshal Department of Electronics & Communication Engineering National Institute of Technology Durgapur India Department of Electrical Engineering National Institute of Technology Durgapur India

In this paper, swarm and evolutionary algorithms have been applied for the design of digital filters. Genetic algorithm (GA) and an improved Particle swarm optimization (PSO) called Particle Swarm Optimization with Constriction Factor and Inertia Weight Approach (PSOCFIWA) have been used here for the design of linear phase band pass finite impulse response (FIR) filters. The fitness function is based on the squared error between the actual and the ideal filter response. PSOCFIWA seems to be promising optimization tool for FIR filter design especially in a dynamic environment where filter coefficients have to be adapted and fast convergence is of importance. Digital filter plays an important role in today's world of communication and computation. On the other hand, to design a digital finite impulse response (FIR) filter satisfying all the required conditions is a challenging one. In this paper, we have introduced an iterative method to find the optimal solution of optimal FIR filter design. FIR filter design is a multi-modal optimization problem. The conventional gradient based optimization techniques are not efficient for digital filter design. Given the filter specification to be realized, PSOCFIWA algorithm generates a set of filter coefficients and tries to meet the ideal frequency characteristic. In this paper, for the given problem, the realization of the FIR band pass filters of different order has been performed. The magnitude responses are demonstrated for the different design techniques of digital FIR filters. The simulation results have been compared with the well accepted evolutionary algorithm such as genetic algorithm (GA). The results justify that the proposed FIR filter design approach using PSOCFIWA outperforms to that of GA, not only in the accuracy of the designed filter but also in the convergence speed and solution quality.

关键词： Finite impulse response filter Band pass filters filtering algorithms Genetic algorithms IIR filters Algorithm design and analysis

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