A new approach of irreqular multifrequency signalprocessing for SW and ultra SW radar is discussed. These signals have advanced noise stability to noise background due to the flexible energy distriibution is spectral...
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ISBN:
(纸本)7505338900
A new approach of irreqular multifrequency signalprocessing for SW and ultra SW radar is discussed. These signals have advanced noise stability to noise background due to the flexible energy distriibution is spectral range. They have improved electromagnetic comparison with another electronic systems. A number of parametric algorithms were synthesized for irregular multifreguency signalprocessing. They are based on autoregressive model using. The results of signal-algorithm approbation are discussed. This approbation was completed with help of experimental SW radar of sea surface monitoring.
In this paper, we report on efforts to develop signalprocessing methods appropriate for the detection of man-made electromagnetic signals in the nonlinear and nonstationary underwater electromagnetic noise environmen...
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ISBN:
(纸本)0819454974
In this paper, we report on efforts to develop signalprocessing methods appropriate for the detection of man-made electromagnetic signals in the nonlinear and nonstationary underwater electromagnetic noise environment of the littoral. Using recent advances in time series analysis methods [Huang et al., 1998], we present new techniques for detection and compare their effectiveness with conventional signalprocessing methods, using experimental data from recent field experiments. These techniques are based on an empirical mode decomposition which is used to isolate signals to be detected from noise without a priori assumptions. The decomposition generates a physically motivated basis for the data.
Detecting cardiac arrhythmias is a significant public health concern, but manual identification and classification of arrhythmias using electrocardiogram (ECG) signals is a challenging task. In this paper, we proposed...
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ISBN:
(纸本)9798350351491;9798350351484
Detecting cardiac arrhythmias is a significant public health concern, but manual identification and classification of arrhythmias using electrocardiogram (ECG) signals is a challenging task. In this paper, we proposed an automatic arrhythmia classification system using Machine Learning and Deep Learning algorithms. The proposed pipeline used a wavelet transform technique to eliminate signal noise. Morphological and statistical features were extracted to classify ECG signal beats into five classes: normal, ventricular, supraventricular, fusion, and paced beats. The system was evaluated on the MIT-BIH arrhythmia database using two classification algorithms, SVM and CNN, achieving accuracy rates of 99.34% and 99.72%, respectively.
In this paper, we present new versions of numerically stable fast recursive least squares (NS-FRLS) algorithms. These new versions are obtained by using some redundant formulae of the fast recursive least squares (FRL...
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ISBN:
(纸本)9780889866751
In this paper, we present new versions of numerically stable fast recursive least squares (NS-FRLS) algorithms. These new versions are obtained by using some redundant formulae of the fast recursive least squares (FRLS) algorithms. Numerical stabilization is achieved by using a propagation model of first order of the numerical errors. A theoretical justification for these versions is presented by formulating new conditions on the forgetting factor. An advanced comparative method is used to study the efficiency of these new versions relatively to RLS algorithm by calculating their squared norm gains ratio (SNGR). The simulation over a very long duration for a stationary signal did not reveal any tendency to divergence.
We review the standard frequency domain methods for modulation classification as a baseline for comparison with new approaches. A new procedure based on the singular value decomposition of a particular data matrix is ...
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ISBN:
(纸本)0819419222
We review the standard frequency domain methods for modulation classification as a baseline for comparison with new approaches. A new procedure based on the singular value decomposition of a particular data matrix is developed. This matrix has some very interesting properties that facilitate a solution of a difficult problem of QPSK versus MSK classification. Performance of the new method is assessed via simulations and compared against those in the published literature.
We(1) highlight potential of advancedsignalprocessingalgorithms for automotive problems of sensing various hard-to-measure quantities. We illustrate virtual sensor capabilities with three examples (misfire detectio...
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ISBN:
(纸本)0780393996
We(1) highlight potential of advancedsignalprocessingalgorithms for automotive problems of sensing various hard-to-measure quantities. We illustrate virtual sensor capabilities with three examples (misfire detection, torque monitor and sensorless detection of changes in tire pressure).
This paper presents an application of formal mathematics to create a high performance, low power architecture for time-frequency and time-scale computations implemented in asynchronous circuit technology that achieves...
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ISBN:
(纸本)0819429163
This paper presents an application of formal mathematics to create a high performance, low power architecture for time-frequency and time-scale computations implemented in asynchronous circuit technology that achieves significant power reductions and performance enhancements over more traditional approaches. Utilizing a combination of concepts from multirate signalprocessing and asynchronous circuit design, a case study is presented dealing with a new architecture for the fast Fourier transform, an algorithm that requires globally shared results. Then, the generalized distributive law is presented as an important paradigm for advanced asynchronous hardware design.
Digital signal processors (DSP) are recently introduced in coherent long-haul optical transmission systems as well as in non-coherent access networks. This contribution reviews a number of specific signalprocessing a...
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ISBN:
(纸本)9781467378802
Digital signal processors (DSP) are recently introduced in coherent long-haul optical transmission systems as well as in non-coherent access networks. This contribution reviews a number of specific signalprocessingalgorithms that are useful in such systems. We focus on advanced equalisers for linear and nonlinear distortions. We examine the Tomlinson-Harashima precoding approach as well as advanced flexible non-integer fractionally-spaced butterfly equalisers. For nonlinearity compensation Volterra based equalization is investigated.
This paper describes a new digital reprogrammable architecture called Field Programmable On-line oPerators (FPOP). This architecture is a kind of FPGA dedicated to very low-power implementations of numerical algorithm...
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ISBN:
(纸本)0819432938
This paper describes a new digital reprogrammable architecture called Field Programmable On-line oPerators (FPOP). This architecture is a kind of FPGA dedicated to very low-power implementations of numerical algorithms in signalprocessing or digital control applications for embedded or portable systems. FPOP is based on a reprogrammable array of on-line arithmetic operators. On-line arithmetic is a digit-serial arithmetic with most significant digits first using a redundant number system. Because of the small size of the digit-serial operators and the small number of communication wires between the operators, single chip implementation of complex numerical algorithms can be achieved using on-line arithmetic. Furthermore, the digit-level pipeline and the small size of the arithmetic operators lead to high-performance parallel computations. Compared to a standard FPGA, the basic cells in FPOP are arithmetic operators such as adders, subtracters, multipliers, dividers, square-rooters, sine or cosine operators. This granularity level allows very efficient power x delay implementations of most algorithms used in digital control and signalprocessing. The circuit also integrates some analog to digital and digital to analog converters.
Searching for wideband short duration chirps is an important issue in spectrum surveillance. We propose a method and apparatus, inspired by optical tomography, by which a one-dimensional signal is converted to a two-d...
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ISBN:
(纸本)0819429163
Searching for wideband short duration chirps is an important issue in spectrum surveillance. We propose a method and apparatus, inspired by optical tomography, by which a one-dimensional signal is converted to a two-dimensional image. This image has the remarkable property that it may disclose discernible structure. A chirp in additive white Gaussian noise, even undersampled, may be detected. The process is inherently linear and may be easily implemented by parallel processing or through the construction of an optoelectronic device.
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