A new concept for solving statistical synthesis problems of radiometric devices and systems (RDS) is developed. The reasonability of using ultra-wideband (UWB) RDSs is substantiated. The basic data of mathematical app...
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A new concept for solving statistical synthesis problems of radiometric devices and systems (RDS) is developed. The reasonability of using ultra-wideband (UWB) RDSs is substantiated. The basic data of mathematical apparatus of V-transforms employed when processing space-time UWB fields and their statistical characteristics is given. A wide class of UWB RDS statistical synthesis problems (compensation, zero-type, modified modulation type, modulation compensation type, multi-antenna systems including cross-correlation-compensation systems and aperture synthesis systems) of stationary and scanning types are solved. The appropriateness of using the Kravchenko weighting functions for refinement of primary radiometric images in radiometric scanning devices is substantiated.
作者:
R.B. WhittedP.B. CrillyCommunications
Information and Signal Processing (CISP) Group Department of Electrical and Computer Engineering University of Tennessee Knoxville TN USA
A VLSI DSP chip is presented that will significantly improve the processing throughput for a general class of iterative deconvolution algorithms. The design will be based on a systolic array concept. This will enable ...
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A VLSI DSP chip is presented that will significantly improve the processing throughput for a general class of iterative deconvolution algorithms. The design will be based on a systolic array concept. This will enable these algorithms to be used for real time DSP applications which formerly due to speed limitations were not possible. The increased class of applications will enable further understanding of these applications. The higher throughput will also enable the researcher to further take advantage of the features unique to iterative deconvolution.< >
A framework for approximate signalprocessing is introduced which can be used to design novel classes of algorithms for performing DFT and STFT calculations. In particular, we focus on the derivation of multi-stage in...
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A framework for approximate signalprocessing is introduced which can be used to design novel classes of algorithms for performing DFT and STFT calculations. In particular, we focus on the derivation of multi-stage incremental refinement algorithms that meet a variety of design criteria on the tradeoff achieved at each stage between solution quality and computational cost.
Presented high-level synthesis describes scheduling for wide class of DSP algorithms. Several FPGA vendors or even ASIC designs are targeted via Handel-C compiled by Celoxica DK3.1 compiler. Using the authors' app...
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Presented high-level synthesis describes scheduling for wide class of DSP algorithms. Several FPGA vendors or even ASIC designs are targeted via Handel-C compiled by Celoxica DK3.1 compiler. Using the authors' approach, the designer can easily change type of used pipelined arithmetic modules and then check new performance. The optimal time schedule is found by cyclic scheduling using integer linear programming while minimizing the schedule period in the terms of clock cycles. Experimental results in HW implementation, performed on logarithmic arithmetic and floating-point arithmetic, confirm significant influence of the period on the resulting performance of DSP algorithms.
A new adaptive algorithm for system identification and adaptive signalprocessing has been proposed in this paper. The algorithm can be viewed as a combination of the output error type and the equation error type of i...
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A new adaptive algorithm for system identification and adaptive signalprocessing has been proposed in this paper. The algorithm can be viewed as a combination of the output error type and the equation error type of identifier (i.e. a combination of IIR adaptive filter and FIR adaptive filter in signalprocessing application). It has been shown both mathematically and by computer simulation that the proposed algorithm can guarantee the globally asymptotical stability under certain regularity conditions on the distribution of signal modes. The transient behaviour of the algorithm is better than conventional output error type of identifier, especially in the case where the system model (signal model) has its eigenvalues on the unit circle. Under certain conditions on the system model (signal model), no moving average (MA) smoothing of the generalized error is needed for the strictly positive realness (SPR) conditions. It gives a reduced bias on the parameter estimate (compare to conventional adaptive FIR filter) when corresponding equation error is a bandlimited process.
The practical application of genetic algorithms (GA) to the solution of engineering problems is a rapidly emerging approach in the field of control engineering and signalprocessing. This tutorial provides a comprehen...
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The practical application of genetic algorithms (GA) to the solution of engineering problems is a rapidly emerging approach in the field of control engineering and signalprocessing. This tutorial provides a comprehensive coverage of the techniques involved, describing the characteristics, advantages and constraints of GA, as well as discussing genetic operations such as crossover, mutation and reinsertion. The intrinsic characteristics in term parallelism, multiobjective, and multimodal etc. are outlined. The features of this approach are illustrated by real-world applications. Also described is a newly proposed and unique hierarchical genetic algorithm designed to address the problem in determining system topology.
This paper presents high-radix CORDIC algorithms for high-speed sine and cosine computation. Since the CORDIC calculation takes O(n) steps for evaluating a function in n-bit precision, significant reduction of process...
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This paper presents high-radix CORDIC algorithms for high-speed sine and cosine computation. Since the CORDIC calculation takes O(n) steps for evaluating a function in n-bit precision, significant reduction of processing latency is required for real-time signalprocessing applications. In this paper, we present a unified approach to low-latency CORDIC implementation based on high-radix algorithms, and propose "radix-2-4-8 CORDIC processor", which achieves low-latency computation by changing radix during execution.
This article deals with fetal electrocardiography (fECG) processing using independent component analysis (ICA). Testing is performed on 7 synthetic recordings with a different level of signal-to-noise ratio (SNR) and ...
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ISBN:
(数字)9781728137292
ISBN:
(纸本)9781728137308
This article deals with fetal electrocardiography (fECG) processing using independent component analysis (ICA). Testing is performed on 7 synthetic recordings with a different level of signal-to-noise ratio (SNR) and the evaluation is performed on calculation of improvement SNR and root mean square error (RMSE). The experiment was based on testing multiple algorithms based on the ICA method, such as the algorithm based on kurtosis value, the algorithm based on negentropy value and the algorithm called kurtosis maximization ICA. The results showed that all ICA-based algorithms a lot improve SNR and have a low value of RMSE, which indicates that signals after filtration are almost similar to the reference signals. All three ICA-based algorithms could be used for fECG extraction, but the lowest accuracy was achieved by the algorithm called kurtosis maximization ICA.
Starting from the viewpoint of linear physical systems, a brief study is presented of energy-conserving or J-orthogonal transformations in a space with an indefinite metric under the special aspect of their VLSI reali...
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Starting from the viewpoint of linear physical systems, a brief study is presented of energy-conserving or J-orthogonal transformations in a space with an indefinite metric under the special aspect of their VLSI realization. A mesh-connected array of n/sup 2/ processor cells, each performing a plane hyperbolic rotation, is shown to be the most natural of n-dimensional subspaces. Isometric linear fractional maps of contractive matrices to the zero matrix and hyperbolic Cholesky factorization are presented as the most interesting applications in generalized Schur methods, digital signalprocessing, and numerical linear algebra. Using the Cholesky factorization as an example, a square-root- and division-free computation scheme for hyperbolic rotations that is highly suited for VLSI implementation is presented.< >
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
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