Grid receivers intend for measuring of spatial-energetic characteristics of laser radiation - intensity distribution, diameter and energetic center coordinates of radiation beams. They contain several wire grids, whic...
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Grid receivers intend for measuring of spatial-energetic characteristics of laser radiation - intensity distribution, diameter and energetic center coordinates of radiation beams. They contain several wire grids, which are standing on way of laser beam. algorithms, which are using for signals processing, are describing.
With the deterioration of radar operation environment and the enhancement of menace to radar, the task of radar target detection becomes more complicated. Such as the detection of airplane, ship or cruise missile in o...
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ISBN:
(纸本)0780378709
With the deterioration of radar operation environment and the enhancement of menace to radar, the task of radar target detection becomes more complicated. Such as the detection of airplane, ship or cruise missile in over the horizon radar (OTHR), and the detection of moving targets in synthetic aperture radar (SAR). Therefore, it is necessary to make a further study of CFAR algorithms. The performance of the conventional cell averaging (CA) algorithm is the best in a homogeneous background since it uses the maximum likelihood estimate of the noise power to set the adaptive threshold. But if the interfering target is present in the reference window with a target return in the test cell, severe masking of targets appears due to increased threshold. In order to overcome this problem, the ordered statistic (OS) and the trimmed mean (TM) algorithms, using a trimmed technique, are proposed. If the reference sample number is not too big, the CFAR loss of OS and TM increase greatly. This case can usually be encountered in a complicated environment and lower SNR situation. In this paper, a weighted window techniques such as rectangle, stepped and trapezium windows are discussed. The analysis results show that the weighted window technique can greatly improve in a homogeneous background and obtain an immune ability to interfering targets to some extent.
Transmit-reference (TR) schemes are commonly used only in low data rate ultra-wideband (UWB) systems because of many restrictions on the pulse spacing, frame and symbol periods (should be longer than the channel lengt...
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Transmit-reference (TR) schemes are commonly used only in low data rate ultra-wideband (UWB) systems because of many restrictions on the pulse spacing, frame and symbol periods (should be longer than the channel length). This paper extends our previous research that tries to remove these restrictions to enable a higher data rate application in a multiuser context. Based on the fact that most UWB channels are highly uncorrelated, we can formulate a CMDA-like signalprocessing model for an asynchronous multiuser system. Blind and iterative algorithms are derived, of which the performances are compared and verified in simulations.
With the rapid advancements in genomics and bioinformatics, gene identification has assumed a pivotal role in contemporary biological research. Gene identification involves pinpointing regions within DNA sequences tha...
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ISBN:
(数字)9798350377255
ISBN:
(纸本)9798350377262
With the rapid advancements in genomics and bioinformatics, gene identification has assumed a pivotal role in contemporary biological research. Gene identification involves pinpointing regions within DNA sequences that encode proteins or functional RNAs, which is of profound significance for understanding the fundamental mechanisms of life, exploring the genetic underpinnings of diseases, and drug development. While traditional experimental biology methods offer reliable tools, they are often time-consuming and costly. Consequently, the application of signalprocessing techniques for gene identification has emerged as a focal point of current research. signalprocessing, with its formidable analytical capabilities when dealing with vast amounts of data, is particularly well-suited for high-dimensional and complex data such as DNA sequences. By converting DNA sequences into numerical signals and employing spectral analysis methods like Fourier and wavelet transforms, intrinsic features of gene structures can be unveiled. Moreover, integrating machine learning algorithms such as Support Vector Machines (SVM) further enhances the accuracy of gene identification. signalprocessing methods provide robust support for the efficient and automated processing of complex genomic data from both prokaryotic and eukaryotic organisms.
In this paper we propose a programming environment that aim to enable fast development and implementation of algorithms for digital signalprocessing on embedded devices. This approach has been verified in education o...
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In this paper we propose a programming environment that aim to enable fast development and implementation of algorithms for digital signalprocessing on embedded devices. This approach has been verified in education of digital signalprocessing.
In this paper we discuss the choice of objective function in list scheduling algorithms for scheduling dataflow graphs onto multiprocessor architectures. A majority of the list scheduling algorithms used in practice u...
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In this paper we discuss the choice of objective function in list scheduling algorithms for scheduling dataflow graphs onto multiprocessor architectures. A majority of the list scheduling algorithms used in practice utilize a global strategy wherein actor static levels are used for making scheduling decisions. When fine grain DSP applications such as FIR or elliptical filters need to be scheduled on architectures that consist of commodity part processors and a general interconnection network whose interprocessor communication cost cannot be ignored, a traditional list scheduling algorithm is in many cases not the best choice. In an experimental study we compare these global strategies to local strategies that utilize load balancing. The study reveals that global strategies suffer from flaws that could cause local strategies to yield more than 10% shorter schedule lengths on the average. In particular we find that a novel Earliest Finish Time (EFT) strategy exhibits very good performance.
作者:
J.S. CastroP. Baylou351
Cours de la Libération Equipe Signal et Image ENSER Bordeaux Talence France
A comparison is made of techniques of parallelization applied to iterative and recursive algorithms. These algorithms are analyzed considering three criteria to generate schedules. These schedules associated with a Bo...
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A comparison is made of techniques of parallelization applied to iterative and recursive algorithms. These algorithms are analyzed considering three criteria to generate schedules. These schedules associated with a Boolean network model, allow the detection of communication conflicts. To reduce conflict possibility, the third criterion is proposed to take into consideration the communication constraints and their influence on the multiprocessor architecture.< >
Previously published results demonstrated that a sequential combination of adaptive linear prediction configuration (LPC), adaptive noise cancellation (ANC), and adaptive comb filtering (CF) can effectively remove mat...
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ISBN:
(数字)9798350354058
ISBN:
(纸本)9798350354065
Previously published results demonstrated that a sequential combination of adaptive linear prediction configuration (LPC), adaptive noise cancellation (ANC), and adaptive comb filtering (CF) can effectively remove maternal interference from noninvasive fetal ECGs. More recent research results have verified that the bio-inspired Lévy Flight Firefly Algorithm (LFFA) can be effectively applied to many different forms of linear and non-linear adaptive filter structures, including low sensitivity IIR adaptive structures that could not be used with steepest descent adaptive algorithms due to their adaptive multimodal characteristics. This paper presents results when using the LFFA algorithm in various stages of the FECG sequential combination processing.
Advanced adaptive signal processing algorithms commonly used in optimization, filtering, and estimation are subjects of seeking innovations and advancements. The important performance factors of algorithms are adaptat...
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ISBN:
(纸本)9781538677421
Advanced adaptive signal processing algorithms commonly used in optimization, filtering, and estimation are subjects of seeking innovations and advancements. The important performance factors of algorithms are adaptation or convergence (the probability of, and the speed of), and computational cost (proportional to the algorithm complexity). The improvement in convergence often comes with higher computational needs. In this report we exploit the diversity in algorithms by using cooperative processes. An odd number of cooperative processes running simultaneously participate in a simple majority-vote decision method to improve the convergence speed of the corresponding application. The iterative algorithms concurrently progressing require higher computational resources, however only the most computationally-efficient algorithm remains active after the initial convergence is achieved. Additional technique is essential to synchronize the process delays of participating algorithms.
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