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检索条件"主题词=Signal processing algorithms"

共 43524 条记录，以下是121-130 订阅

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HIPED: a tool for high-level power estimation of digital signal processing algorithms

HIPED: a tool for high-level power estimation of digital sig...

引用

IEEE International Conference on Electronics, Circuits and Systems (ICECS)

作者： I. Ben Dhaou H. Tenhunen Department of Microelectronics and Information Technology Royal Institute of Technology Sweden

This paper describes HIPED, a tool for fast power estimation of DSP algorithms given its data-flow graph representation. Each node of the DFG is characterized for low-power using LP-DSM. In order to estimate the power consumption of the DSP, HIPED computes the entropy of the data transferred between two computational nodes. The entropy, which measures the data-activity of the circuit, is subsequently used by the power macro-model to predict the power consumption of the sink node. The total power consumption is thus obtained by summing up the power consumption of each node of the DFG. HIPED is used to estimate the power consumption of a variety of DSP algorithms used in typical wireless receivers implemented in 0.35 /spl mu/m, 3.3 V CMOS process. The characterization process of arithmetic units implements both using SPL and CMOS circuit style showed that LP-DSM has lower prediction sum of error and lower error in cycle power than Gupta's algorithm. Furthermore, the simulation results using real data showed that HIPED has a very good accuracy compared to circuit level power reported by PowerMill. The observed average error of our benchmark circuits is less than 10%.

关键词： Digital signal processing signal processing algorithms Circuits Energy consumption Iterative algorithms Libraries CMOS process Discrete wavelet transforms Image coding Maximum likelihood decoding

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Light-weight single trial EEG signal processing algorithms: Computational profiling for low power design

Light-weight single trial EEG signal processing algorithms: ...

引用

Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Ali Ahmadi Roozbeh Jafari John Hart Embedded Systems and Signal Processing Lab Department of Electrical Engineering University of Texas Dallas Richardson TX USA Center of Brain Health University of Texas Dallas Dallas TX USA

Brain Computer Interface (BCI) systems translate brain rhythms into signals comprehensible by computers. BCI has numerous applications in the clinical domain, the computer gaming, and the military. Real-time analysis of single trial brain signals is a challenging task, due to the low SNR of the incoming signals, added noise due to muscle artifacts, and trial-to-trial variability. In this work we present a computationally lightweight classification method based on several time and frequency domain features. After preprocessing and filtering, wavelet transform and Short Time Fourier Transform (STFT) are used for feature extraction. Feature vectors which are extracted from θ and α frequency bands are classified using a Support Vector Machine (SVM) classifier. EEG data were recorded from 64 electrodes during three different Go/NoGo tasks. We achieved 91% classification accuracy for two-class discrimination. The high recognition rate and low computational complexity makes this approach a promising method for a BCI system running on wearable and mobile devices. Computational profiling shows that this method is suitable for real time signal processing implementation.

关键词： Electroencephalography Feature extraction Support vector machines signal processing algorithms Classification algorithms signal processing Accuracy

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Mobile stethoscope and signal processing algorithms for pulmonary screening and diagnostics

Mobile stethoscope and signal processing algorithms for pulm...

引用

IEEE Global Humanitarian Technology Conference (GHTC)

作者： D. Chamberlain J. Mofor R. Fletcher R. Kodgule Edgerton Center D-Lab Massachusetts Institute of Technology Cambridge MA USA Chest Research Foundation Pune India

Pulmonary diseases represent a large disease burden in terms of morbidity and mortality worldwide. For many reasons, including household air pollution and a shortage of trained doctors, this burden is concentrated in the developing world. The standard diagnostic pathway for pulmonary diseases is prohibitively expensive in developing countries, so these diseases are often misdiagnosed or underdiagnosed. To assist doctors and health workers, there is a need to create tools that can automatically recognize specific lung sounds and provide diagnostic guidance. As a first step towards this long-term goal, we have created a low-cost stethoscope and smartphone application to record lung sounds. We discuss problems we encountered with the initial design and demonstrate an improved design that is currently being used in the field. We also demonstrate an algorithm capable of automatic detection of wheeze sounds. The automatic wheeze detection algorithm uses time-frequency analysis and the Short Time Fourier Transform to identify sections of wheezing in recorded lung sound files. Unlike most published sound classification studies, we trained and tested our algorithms using sound data collected from 38 actual patients at a pulmonary clinic in Pune, India. Despite variability in the quality of the data, our algorithm demonstrated an accuracy of 86% for successfully detecting the presence of wheeze in a sound file. This mobile platform and detection algorithm demonstrates an important step in creating an automated platform for the diagnosis of pulmonary diseases in a real-world setting.

关键词： Stethoscope Lungs Diseases signal processing algorithms Classification algorithms Mobile communication

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Performance analysis of signal processing algorithms using multi-core DSP platform

Performance analysis of signal processing algorithms using m...

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IEEE signal processing and Communications Applications (SIU)

作者： Emrah Şapla Ömer Faruk Gemici Ibrahim Hökelek Tübitak Bölgem Ulusal Elektronik ve Kriptoloji Arastirma Enstitusu Kocaeli TR

signal processing applications in next generation radar and communication systems have enormous processing capacity requirements. Multi-core processor technologies have been widely used in order to meet these huge processing capacity needs. In this paper, edge detection, low pass filter, and fast Fourier transform algorithms has been developed on Texas Instruments TCI6630K2L system on chip device by efficiently utilizing the multi-core architecture. We present the performance results of these algorithms with respect to the number of DSP cores and the picture size. For all experiments, the image processing time decreases consistently when the number of DSP cores increases; however, the performance improvement rate varies according to the signal processing algorithm type and the picture size. Having the performance improvement rates independent of the picture size indicates that the processing power spent for data transmission between ARM and DSP is neglible compared to the processing power spent for signal processing algorithms.

关键词： Multicore processing Digital signal processing signal processing algorithms Radar Performance evaluation Art Conferences

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Wavelet based signal processing algorithms for early target detection

Wavelet based signal processing algorithms for early target ...

引用

IEEE Region 10 International Conference TENCON

作者： S.J. Thiruvengadam P. Chinnadurai M.T. Thirumalai Kumar V. Abhaikumar Signal Processing Laboratory Department of Electronics and Communication Engineering Thiagarajar College of Engineering Madurai Tamil Nadu India

Detection of radar target earlier, that is, at a longer distance, amidst noise is a major issue since the received echo signal has very low input signal to noise ratio of the received signal. Further, it becomes very difficult due to unknown statistics and nonstationary nature of the received signal. This paper deals with the wavelet based signal processing algorithms which could detect target even with very weak received signal. Since the signals with identical spectra may have different time-frequency image in time-frequency domain. The algorithms use optimum bandwidth relative to the signal spectral width to maximize the output signal to noise ratio and hence probability of detection. Simulation results show that the wavelet filtering algorithm and entropy based basis algorithms are able to detect target from the input signal to noise ratio of -10dB.

关键词： signal processing algorithms Object detection signal to noise ratio Time frequency analysis Radar detection Statistics signal processing Bandwidth Filtering algorithms Entropy

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A framework for automatic large-scale testing and characterization of signal processing algorithms

A framework for automatic large-scale testing and characteri...

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MILCOM, Military Communications Conference

作者： K. Holladay K.A. Robbins Southwest Research Institute San Antonio TX USA University of Texas San Antonio San Antonio TX USA

Performance analysis of signal processing algorithms should yield insight into expected performance as a function of all varying factors including algorithm parameters, signal characteristics, and transmission channel propagation effects. This paper presents a test framework for characterizing signal processing algorithm behavior. The framework provides functions to automate the evaluation process including creating large numbers of test files, running these files through the algorithm under test, collecting data, and analyzing the results. Automating this cycle allows rapid testing and evaluation of algorithm enhancements, as well as identifying the significant factors that affect performance. We demonstrate this technique by comparing and characterizing two different published symbol rate estimation algorithms.

关键词： Large-scale systems Automatic testing signal processing algorithms Algorithm design and analysis Performance analysis Data analysis signal analysis Digital signal processing System testing signal processing

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FPGA-based 112Gb/s coherent DP-QPSK receiver and multi-stage PMD-PDL emulator for fast evaluation of digital signal processing algorithms

FPGA-based 112Gb/s coherent DP-QPSK receiver and multi-stage...

引用

European Conference on Optical Communication (ECOC)

作者： Takahito Tanimura Yasuhiko Aoki Hisao Nakashima Takeshi Hoshida Jianqiang Li Zhenning Tao Jens C. Rasmussen Fujitsu Laboratories Limited Kawasaki Japan Fujitsu Research and Development Center Company Limited Beijing China

We developed an FPGA based 112Gb/s coherent DP-QPSK receiver and a multi-stage PMD-PDL emulator that resembles real fibre conditions. Long-term, low penalty signal reception under severe PMD (31.2ps mean) and PDL (1.3... 详细信息

关键词： Receivers signal processing algorithms Frequency measurement Digital signal processing Couplings Frequency control Q measurement

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Battery-friendly design of signal processing algorithms

Battery-friendly design of signal processing algorithms

引用

IEEE Workshop on signal processing Systems (SIPS)

作者： P. Raghavan C. Chakrabarti Arizona State University AZ USA

Portable systems today are designed with lowering the energy consumption as the primary design metric. This is unfortunate, since maximizing battery lifetime is a more appropriate metric, and lowering energy does not necessarily mean improving battery lifetime. We first show how to design battery-friendly implementations of common signal processing kernels such as FIR filters and FFT. The basic idea is to generate a load profile that results in better battery behavior. Next, we demonstrate how frequency scaling can be used effectively to improve the battery behavior of an application such as MPEG2.

关键词： Batteries Process design signal design Algorithm design and analysis signal processing algorithms Energy consumption Voltage Kernel Finite impulse response filter Frequency

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Digital signal processing and algorithms for gamma-ray tracking

Digital signal processing and algorithms for gamma-ray track...

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IEEE Symposium on Nuclear Science (NSS/MIC)

作者： W. Gast R.M. Lieder L. Mihailescu M.J. Rossewij H. Brands A. Georgiev J. Stein Th. Kroll Forschungszentrum Julich GmbH Germany Forschungszentrum Jülich IKP Julich Germany Target systemelectronic gmbh Solingen Germany Sezione di Padova I.N.F.N. Padova Italy

Gamma-ray tracking is a new concept to improve efficiency and sensitivity of the next generation, high resolution /spl gamma/-ray spectrometers. Tracing multiple scattered /spl gamma/-rays inside an array of large volume composite, segmented Ge-detectors, the photo energies of the individual /spl gamma/-rays and their incident directions can be precisely reconstructed. This results in an improved efficiency and peak-to-total ratio, and a reduced Doppler-broadening. The reconstruction efficiency depends on how accurate the positions, where the /spl gamma/-rays interact with the Ge-crystals, can be localized. Novel digital signal processing hardware modules and related software algorithms are described, which allow an on-line determination of the energies, times, and interaction positions of the /spl gamma/-rays by analyzing the shapes of the charge signals induced on the segments.

关键词： Digital signal processing signal processing algorithms signal resolution Spectroscopy Scattering Hardware Software algorithms signal analysis Algorithm design and analysis Shape

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Time-frequency signal processing: methods and algorithms

Time-frequency signal processing: methods and algorithms

引用

International Symposium on signal processing and Its Applications (ISSPA)

作者： B. Boashash Queensland University of Technology Australia

Summary form only given, as follows. The tutorial presents the fundamental principles applied in analysing non-stationary signals, and the current methods developed to deal with this class of signals. It shows the lin... 详细信息

关键词： signal processing algorithms Time frequency analysis signal analysis Spectral analysis

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