The separation of noise from speech signals has always been a necessary requirement and is being demanded in speech signalprocessing applications as an important factor to achieve clear speech while communicating. In...
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The separation of noise from speech signals has always been a necessary requirement and is being demanded in speech signalprocessing applications as an important factor to achieve clear speech while communicating. In the last decade, some research on the separation of speech and noise has been published. In previous research work some traditional algorithms were used, such as least mean squares, the nearest neighbour and the quadratic Gaussian algorithms. This paper provides an extensive experimental simulation of speech with and without noise to solve the filtering problem. An FIR digital filter is designed and proposed to train a neural network. The experimental results show that using neural networks in noise separation produce a more robust and powerful separation of speech and noise than other traditional algorithms. Furthermore, the FIR digital filter provides a fast convergence and gives results near the global optimal. The neural networks such as Elman, radial base function and perceptron networks are trained with different training algorithms and compared with the performance of FIR digital filter including its computational complexity. It is found that an algorithm chosen to train the neural network is very important to the final results
In this paper we presents the information about classification and realization of the combined signal processing algorithms. The short analysis of algorithms performances are implemented.
In this paper we presents the information about classification and realization of the combined signal processing algorithms. The short analysis of algorithms performances are implemented.
This article presents the results of analysis of measuring ECG signals processing using two new filtering algorithms for low-frequency and high-frequency interference. The presence of such interferences leads to a dec...
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ISBN:
(数字)9781665404761
ISBN:
(纸本)9781665446426
This article presents the results of analysis of measuring ECG signals processing using two new filtering algorithms for low-frequency and high-frequency interference. The presence of such interferences leads to a decrease in the accuracy of the selection of informative components of the measuring signals. To eliminate low-frequency and high-frequency interference, the results of evaluating the effectiveness of two new algorithms for ECG signals are presented. The processingalgorithms are based on a polynomial approximation of the high-pass filter and the wide-band notch filter cascade using Newton polynomials. On the basis of these processingalgorithms, its performance was analyzed on a priori models of ECG signals and interference, and on the basis of quantitative indicators, its effectiveness was compared with respect to known algorithms. It was found that processingalgorithms based on Newton polynomials significantly improve the quality of filtering of measuring ECG signals and indicators of signal-to-noise ratio and mean square error.
In this paper a family of so-called anytime signal processing algorithms is introduced to improve the overall performance of larger scale embedded digital signalprocessing (DSP) systems. In such systems there are cas...
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In this paper a family of so-called anytime signal processing algorithms is introduced to improve the overall performance of larger scale embedded digital signalprocessing (DSP) systems. In such systems there are cases where due to abrupt changes within the environment and/or the processing system temporal shortage of computational power and/or loss of some data may occnr. It is an obvious requirement that even in such situations the actual processing should be continued to insure appropriate performance. This means that signalprocessing of somewhat simpler complexity should provide outputs of acceptable quality to continue the operation of the complete embedded system. The accuracy of the processing will be temporarily lower but possibly still enough to produce data for qualitative evaluations and supporting decisions. Consequently anytime algorithms should provide short response time and be very flexible with respect to the available input information and computational power. The paper presents such algorithms based on the re-configurable version of the recursive signal transformer structure described in [1].
This paper presents the application of genetic algorithms to the on-line adaptation of non-linear adaptive filters-adaptive systems applicable to, for example, stochastic signal estimation, system identification and t...
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This paper presents the application of genetic algorithms to the on-line adaptation of non-linear adaptive filters-adaptive systems applicable to, for example, stochastic signal estimation, system identification and the optimization of electronic or optoelectronic signal processors. Given the filter topology, the corresponding filter parameters are estimated using a time-dependent moving error criterion. The genetic algorithm's ability to track temporal changes in the signal statistics is achieved by the use of partial hypermutation. The proposed methodology is applied to the problem of non-linear and non-stationary signal estimation by using the adaptive filter as part of a non-linear prediction error filter. Simulation results for the estimation of autoregressive and bilinear stochastic signal models and a comparison to the least mean squares algorithm are presented demonstrating the suitability of the approach.
I introduce SPIRAL (***), a generator of libraries of linear signal processing algorithms like linear transforms, including the discrete Fourier transform, the discrete cosine transform, filters, or wavelets, as well ...
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I introduce SPIRAL (***), a generator of libraries of linear signal processing algorithms like linear transforms, including the discrete Fourier transform, the discrete cosine transform, filters, or wavelets, as well as applications lke JPEG2000, Viterbi decoding, and SAR image formation algorithms. SPIRAL is a new breed of intelligent compilers that couples domain knowledge, computer architecture modeling, machine learning methodologies, and compiler technology to generate automatically highly tuned SW codes and very efficient HW IP cores. SPIRAL produces automatically C code with embedded vector and parallel instructions for multicore or multiprocessor architectures, or netlists for FPGA implementations. SPIRAL can optimize for or trade among a range of criteria including runtime, power/energy, accuracy, or area. SPIRAL has been benchmarked against expert hand tuned implementations and has been licensed as a tool by INTEL.
This paper describes the signal processing algorithms that can be used for the PMUs operating in a dynamic environment. Dynamic response and rejection to noise, harmonics and interharmonics are discussed and some solu...
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ISBN:
(纸本)9781467391351
This paper describes the signal processing algorithms that can be used for the PMUs operating in a dynamic environment. Dynamic response and rejection to noise, harmonics and interharmonics are discussed and some solutions for improving them, emerging from the technical literature and from some additional tests, are proposed. For example dynamic response can be improved by evaluating the Taylor series as a time function, while the rejection to harmonics by selecting appropriately the observation time.
The present paper deals with a new, computationally efficient, algorithm for Sequential Least Squares (LS) estimation. This scheme requires only O(5p) MAD (Multiplications And Divisions) per recursion to update a Kalm...
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The present paper deals with a new, computationally efficient, algorithm for Sequential Least Squares (LS) estimation. This scheme requires only O(5p) MAD (Multiplications And Divisions) per recursion to update a Kalman type gain vector; p is the number of estimated parameters. In contrast the well-known fast Kalman algorithm requires O(8p) MAD. The introduced method is the fastest known algorithm featured by the rapid convergence characteristics of exact Least Squares estimation schemes. Another interesting feature of the new algorithm is the balanced role, the forward and backward prediction play.
algorithms estimate the parameters of UWB radiothermal signals in single-antenna radiometers with modulation are synthesized and investigated within the bounds of method of maximum likelihood. Based on analysis of the...
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algorithms estimate the parameters of UWB radiothermal signals in single-antenna radiometers with modulation are synthesized and investigated within the bounds of method of maximum likelihood. Based on analysis of the matrix inverse to the Fisher in- formation matrix the potential accuracy of estimates of measured parameters and the sensitivity of radiometric systems are investigated.
The purpose of the work is to substantiate the possibility traveling wave fault location (TWFL) complex functioning in branched distribution networks of medium voltage class. Traveling waves (TW) are born in the place...
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ISBN:
(数字)9798350386028
ISBN:
(纸本)9798350386035
The purpose of the work is to substantiate the possibility traveling wave fault location (TWFL) complex functioning in branched distribution networks of medium voltage class. Traveling waves (TW) are born in the place of fault. The complex registers the time of TW arrival to the ends of the network in a unified satellite time scale. Then the complex calculates the fault location. The main factor complicating the complex's functioning in branched networks of medium voltage class lines is the presence of a large number of concentrated inhomogeneities in the form of nodes with branches. Analytically and with the help of model calculations in PSCAD program, we can obtain TW transmission coefficient through inhomogeneity nodes at different types of faults. The paper shows the experiments' results. A large number of complex's sensors in several ends of the branched network allows us to determine the time TW registration and the speed of their propagation along the lines between paired combinations complex's sensors. Comparison of the registered propagation speed with the speed of light allows us to separate reliable or accurate registrations of the TW beginning from unreliable registrations. It is shown, that the amplitude of the registered TW and the amplitude of stationary and non-stationary noise at the place of registration determine the reliability of the complex operation. The paper compares the results of TW registration generated inside and outside the area controlled by the complex.
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