Channel estimation is one of the most important questions in digital mobile communications. In 1998, Abets S et al. proposed the weighted multislot averaging (WMSA) method to improve the transmission performance. In t...
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Channel estimation is one of the most important questions in digital mobile communications. In 1998, Abets S et al. proposed the weighted multislot averaging (WMSA) method to improve the transmission performance. In this paper, a new channel estimation method based on fuzzy system was suggested to further improve the tracking performance against fast fading. The fuzzy modeling technique was utilized to estimate the data channel, and the lms algorithm was applied to adaptively estimate the parameters. Based on the fact that fuzzy system is very useful for function approximation, our method is superior to WMSA in BER performance under fast mobile traveling speeds.
IoT is the big buzzword in today's technical fraternity. The implementation of 5G networks is also up in urban areas. This is perhaps fortunate from an IoT perspective, as IoT's main applications will realize ...
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IoT is the big buzzword in today's technical fraternity. The implementation of 5G networks is also up in urban areas. This is perhaps fortunate from an IoT perspective, as IoT's main applications will realize Smart automated cities' dream. Enhanced mobile broadband (eMBB)-based services are far and wide dependent upon the bandwidth requirement for effective communication in Smart City applications. Modern-day signal processing techniques are widely reliant on adaptive filters for efficient applications like signal prediction, echo cancellation, noise cancellation, etc. In this work, the use of adaptive filters is performed for stationary and nonstationary signals. It is well known that adaptive filters' performance and effect depend on their regulating parameters and noise variance. Therefore, the parameter step size and filter orders are varied, and the outcome of the variations on respective signals is noted. Simulation of these scenarios is discussed at length to ensure better insight of adaptive filters to researchers and engineers to select the appropriate filter for a specific application.
Electrocardiogram (ECG) is an electrical signal detected by the particular device and method. It is very important to analyze and measure ECG for diagnosis of various heart diseases. However, it is often disturbed by ...
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Electrocardiogram (ECG) is an electrical signal detected by the particular device and method. It is very important to analyze and measure ECG for diagnosis of various heart diseases. However, it is often disturbed by different types of noise. In this paper, an adaptive morphological filter is presented to remove the power line interference from ECG signals, by which the drawbacks of previous morphological method are overcome. Moreover, the extraction of R peak in ECG is also feasible by this filter for further study on ECG. Due to the high speed of our method, the ECG de-nosing and R Peak extracting could be both realized at real time, which is an effective method to monitoring patients undergoing surgeries.
The blind Bussgang algorithms are considered in this paper. They use statistical properties of the transmitted symbols to elimination of the channel distortions. The main advantage of the Bussgang methods is simplicit...
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The blind Bussgang algorithms are considered in this paper. They use statistical properties of the transmitted symbols to elimination of the channel distortions. The main advantage of the Bussgang methods is simplicity of their implementations. They are based on the classical approach called the lms algorithm. Simulation results show thetypical equalization properties and possibilities for selected algorithms depending on the channel characteristic, the adaptation step and the equalizer order. Presented results concern thelinear channel equalization.
In this paper, a least Incosh (Llncosh) algorithm is derived by utilizing the Incosh cost function. The Incosh cost is characterized by the natural logarithm of hyperbolic cosine function, which behaves like a hybrid ...
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In this paper, a least Incosh (Llncosh) algorithm is derived by utilizing the Incosh cost function. The Incosh cost is characterized by the natural logarithm of hyperbolic cosine function, which behaves like a hybrid of the mean square error (MSE) and mean absolute error (MAE) criteria depending on adjusting a positive parameter A. Hence, the Llncosh algorithm performs like the least mean square (lms) algorithm for small errors and behaves as the sign-error lms (Slms) algorithm for large errors. It provides comparable performance to the lms algorithm in Gaussian noise. When compared with several existing robust approaches, the superior steady-state performance and stronger robustness can be attained in impulsive noise. The mean behavior, mean-square behavior and steady-state performance analyses of the proposed algorithm are also provided. In addition, aiming to acquire a compromise between fast initial convergence rate and satisfactory steady-state performance, we introduce a variable-A Llncosh (VLlncosh) scheme. Lastly, in order to resist the sparsity of the acoustic echo path, an improved proportionate least Incosh (PLlncosh) algorithm is presented. The good performance against impulsive noise and theoretical results of the proposed algorithm are validated by simulations. (C) 2019 Elsevier B.V. All rights reserved.
This work focuses on the development of a new family of decision-making algorithms for adaptation and learning, which are specifically tailored to decision problems and are constructed by building up on first principl...
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This work focuses on the development of a new family of decision-making algorithms for adaptation and learning, which are specifically tailored to decision problems and are constructed by building up on first principles from decision theory. A key observation is that estimation and decision problems are struc-turally different and, therefore, algorithms that have proven successful for the former need not perform well when adjusted for the latter. Exploiting classical tools from quickest detection, we propose a tailored version of Page's test, referred to as BLLR (barrier log-likelihood ratio) test, and demonstrate its applica-bility to real-data from the COVID-19 pandemic in Italy. The results illustrate the ability of the design tool to track the different phases of the outbreak.(c) 2021 Published by Elsevier B.V.
This paper proposes a realization of a two-dimensional adaptive state-space filter for parallel processing using state-space model with a general form. For the modeling of the filter, a generalized model realized for ...
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This paper proposes a realization of a two-dimensional adaptive state-space filter for parallel processing using state-space model with a general form. For the modeling of the filter, a generalized model realized for parallel processing is used and the conventional denominator-separation type model is extended. Further, the lms (Least Mean Square) algorithm is used to construct an adaptive algorithm and its processing speed and computational effort are evaluated. By means of this method, the hardware content can be reduced while the processing speed is maintained almost the same as in the complete generalized model. Finally, in order to verify the effectiveness of the present method, an example is presented in which a two-dimensional adaptive filter is applied to the spatial domain design as a system identification problem. (C) 2002 Wiley Periodicals, Inc.
This paper describes pipeline realization of a gradient-type adaptive filter on the algorithmic level. By pipeline realization, the longest path (critical path) of the filter can be reduced so that the throughput char...
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This paper describes pipeline realization of a gradient-type adaptive filter on the algorithmic level. By pipeline realization, the longest path (critical path) of the filter can be reduced so that the throughput characteristic can be improved. In addition, the reduction of the critical path relaxes the restriction on the operators to be used and the power consumption can be decreased. Evaluation criteria of the pipeline realization are throughput, convergence, latency, and computational complexity. Using the delayed lms adaptive filter as one of the gradient-type adaptive filters, it is shown that pipeline realization is possible that not only has a high throughput but also convergence and latency identical to those in the lms adaptive filter taking into account the hardware complexity. (C) 2001 Scripta Technica.
The wavelet shrinkage method is a nonlinear signal denoising procedure to remove noise by shrinking the empirical wavelet coefficients in the wavelet domain. In this paper, we apply the wavelet shrinkage method to non...
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The wavelet shrinkage method is a nonlinear signal denoising procedure to remove noise by shrinking the empirical wavelet coefficients in the wavelet domain. In this paper, we apply the wavelet shrinkage method to nonlinear adaptive digital filters, and we propose the adaptive wavelet shrink-age filter which updates the threshold levels adaptively by the lms algorithm according to the reference signal. The adaptive wavelet shrinkage filter is robust and has the property that one can control the filter easily by modifying the threshold levels. We describe the theorems concerning the convergence of the lms algorithm for updating the threshold levels, and demonstrate several examples of the adaptive wavelet shrinkage Filter. (C) 2002 Wiley Periodicals, Inc.
Cílem této diplomové práce bylo seznámit se s problematikou metod adaptivní filtrace a jejich využití pro potlačení rušení v biologických signálech. Adaptivní...
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Cílem této diplomové práce bylo seznámit se s problematikou metod adaptivní filtrace a jejich využití pro potlačení rušení v biologických signálech. Adaptivní filtrace představuje efektivní způsob potlačení parazitního nestacionárního rušení v užitečném signálu. Úkolem bylo navrhnout různé typy adaptivních filtrů a realizovat algoritmus adaptace v programovém prostředí Matlab. Konkrétně se jednalo o potlačení síťového rušení v EKG signálech o kmitočtu 50 Hz a 100 Hz s minimalizací porušení užitečné složky. Realizované filtry byly ověřeny na reálných EKG signálech a byla vyhodnocena jejich účinnost.
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