68 resultados para discrete wavelet transform


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Wavelets introduce new classes of basis functions for time-frequency signal analysis and have properties particularly suited to the transient components and discontinuities evident in power system disturbances. Wavelet analysis involves representing signals in terms of simpler, fixed building blocks at different scales and positions. This paper examines the analysis and subsequent compression properties of the discrete wavelet and wavelet packet transforms and evaluates both transforms using an actual power system disturbance from a digital fault recorder. The paper presents comparative compression results using the wavelet and discrete cosine transforms and examines the application of wavelet compression in power monitoring to mitigate against data communications overheads.

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Eight thousand images of the solar corona were captured during the June 2001 total solar eclipse. New software for the alignment of the images and an automated technique for detecting intensity oscillations using multi-scale wavelet analysis were developed. Large areas of the images covered by the Moon and the upper corona were scanned for oscillations and the statistical properties of the atmospheric effects were determined. The a Trous wavelet transform was used for noise reduction and Monte Carlo analysis as a significance test of the detections. The effectiveness of those techniques is discussed in detail.

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The global increase in the penetration of renewable energy is pushing electrical power systems into uncharted territory, especially in terms of transient and dynamic stability. In particular, the greater penetration of wind generation in European power networks is, at times, displacing a significant capacity of conventional synchronous generation with fixed-speed induction generation and now more commonly, doubly fed induction generators. The impact of such changes in the generation mix requires careful monitoring to assess the impact on transient and dynamic stability. This study presents a measurement-based method for the early detection of power system oscillations, with consideration of mode damping, in order to raise alarms and develop strategies to actively improve power system dynamic stability and security. A method is developed based on wavelet-based support vector data description (SVDD) to detect oscillation modes in wind farm output power, which may excite dynamic instabilities in the wider system. The wavelet transform is used as a filter to identify oscillations in frequency bands, whereas the SVDD method is used to extract dominant features from different scales and generate an assessment boundary according to the extracted features. Poorly damped oscillations of a large magnitude, or that are resonant, can be alarmed to the system operator, to reduce the risk of system instability. The proposed method is exemplified using measured data from a chosen wind farm site.

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This paper is concerned with the universal (blind) image steganalysis problem and introduces a novel method to detect especially spatial domain steganographic methods. The proposed steganalyzer models linear dependencies of image rows/columns in local neighborhoods using singular value decomposition transform and employs content independency provided by a Wiener filtering process. Experimental results show that the novel method has superior performance when compared with its counterparts in terms of spatial domain steganography. Experiments also demonstrate the reasonable ability of the method to detect discrete cosine transform-based steganography as well as the perturbation quantization method.

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Aim: Two Type I diabetes and control group comparator studies were conducted to assess the reproducibility of FMD and to analyse blood flow data normally discarded during FMD measurement.

Design: The studies were sequential and differed only with regard to operator and ultrasound machine. Seventy-two subjects with diabetes and 71 controls were studied in total.

Methods: Subjects had FMD measured conventionally. Blood velocity waveforms were averaged over 10 pulses post forearm ischaemia and their component frequencies analysed using the wavelet transform, a mathematical tool for waveform analysis. The component frequencies were grouped into 11 bands to facilitate analysis.

Results: Subjects were well-matched between studies. In Study 1, FMD was significantly impaired in subjects with Type I diabetes vs. controls (median 4.35%, interquartile range 3.10-4.80 vs. 6.50, 4.79-9.42, P < 0.001). No differences were detected between groups in Study 2, however. However, analysis of blood velocity waveforms yielded significant differences between groups in two frequency bands in each study.

Conclusions: This report highlights concerns over the reproducibility of FMD measures. Further work is required to fully elucidate the role of analysing velocity waveforms after forearm ischaemia.

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Objective: Waveform analysis has been used to assess vascular resistance and predict cardiovascular events. We aimed to identify microvascular abnormalities in patients with impaired glucose tolerance (IGT) using ocular waveform analysis. The effects of pioglitazone were also assessed. Methods: Forty patients with IGT and twenty-four controls were studied. Doppler velocity recordings were obtained from the central retinal, ophthalmic and common carotid arteries, and sampled at 200 Hz. A discrete wavelet-based analysis method was employed to quantify waveforms. The resistive index (RI),was also determined. Patients with IGT were randomised to pioglitazone or placebo and measurements repeated after 12 weeks treatment. Results: In the ocular waveforms, significant differences in power spectra were observed in frequency band four (corresponding to frequencies between 6.25 and 12.50 Hz) between groups (p

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This implementation of a two-dimensional discrete cosine transform demonstrates the development of a suitable architectural style for a specific technology-in this case, the Xilinx XC6200 FPGA series. The design exploits distributed arithmetic, parallelism, and pipelining to achieve a high-performance custom-computing implementation.

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Automatic gender classification has many security and commercial applications. Various modalities have been investigated for gender classification with face-based classification being the most popular. In some real-world scenarios the face may be partially occluded. In these circumstances a classification based on individual parts of the face known as local features must be adopted. We investigate gender classification using lip movements. We show for the first time that important gender specific information can be obtained from the way in which a person moves their lips during speech. Furthermore our study indicates that the lip dynamics during speech provide greater gender discriminative information than simply lip appearance. We also show that the lip dynamics and appearance contain complementary gender information such that a model which captures both traits gives the highest overall classification result. We use Discrete Cosine Transform based features and Gaussian Mixture Modelling to model lip appearance and dynamics and employ the XM2VTS database for our experiments. Our experiments show that a model which captures lip dynamics along with appearance can improve gender classification rates by between 16-21% compared to models of only lip appearance.

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A bit-level systolic array for computing matrix x vector products is described. The operation is carried out on bit parallel input data words and the basic circuit takes the form of a 1-bit slice. Several bit-slice components must be connected together to form the final result, and authors outline two different ways in which this can be done. The basic array also has considerable potential as a stand-alone device, and its use in computing the Walsh-Hadamard transform and discrete Fourier transform operations is briefly discussed.

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The use of bit-level systolic arrays in the design of a vector quantized transformed subband coding system for speech signals is described. It is shown how the major components of this system can be decomposed into a small number of highly regular building blocks that interface directly to one another. These include circuits for the computation of the discrete cosine transform, the inverse discrete cosine transform, and vector quantization codebook search.

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A number of high-performance VLSI architectures for real-time image coding applications are described. In particular, attention is focused on circuits for computing the 2-D DCT (discrete cosine transform) and for 2-D vector quantization. The former circuits are based on Winograd algorithms and comprise a number of bit-level systolic arrays with a bit-serial, word-parallel input. The latter circuits exhibit a similar data organization and consist of a number of inner product array circuits. Both circuits are highly regular and allow extremely high data rates to be achieved through extensive use of parallelism.

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The design of a System-on-a-Chip (SoC) demonstrator for a baseline JPEG encoder core is presented. This combines a highly optimized Discrete Cosine Transform (DCT) and quantization unit with an entropy coder which has been realized using off-the-shelf synthesizable IP cores (Run-length coder, Huffman coder and data packer). When synthesized in a 0.35 µm CMOS process, the core can operate at speeds up to 100 MHz and contains 50 k gates plus 11.5 kbits of RAM. This is approximately 20% less than similar JPEG encoder designs reported in literature. When targeted at FPGA the core can operate up to 30 MHz and is capable of compressing 9-bit full-frame color input data at NTSC or PAL rates.

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Details are presented of the IRIS synthesis system for high-performance digital signal processing. This tool allows non-specialists to automatically derive VLSI circuit architectures from high-level, algorithmic representations, and provides a quick route to silicon implementation. The applicability of the system is demonstrated using the design example of a one-dimensional Discrete Cosine Transform circuit.

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The global increase in the penetration of renewable energy is pushing electrical power systems into uncharted territory, especially in terms of transient and dynamic stability. In particular, the greater penetration of wind generation in European power networks is, at times, displacing a significant capacity of conventional synchronous generation with fixed-speed induction generation and now more commonly, doubly-fed induction generators. The impact of such changes in the generation mix requires careful monitoring to assess the impact on transient and dynamic stability. This paper presents a measurement based method for the early detection of power system oscillations, with attention to mode damping, in order to raise alarms and develop strategies to actively improve power system dynamic stability and security. A method is developed based on wavelet transform and support vector data description (SVDD) to detect oscillation modes in wind farm output power, which may excite dynamic instabilities in the wider system. The wavelet transform is used as a filter to identify oscillations in different frequency bands, while SVDD is used to extract dominant features from different scales and generate an assessment boundary according to the extracted features. Poorly damped oscillations of a large magnitude or that are resonant can be alarmed to the system operator, to reduce the risk of system instability. Method evaluation is exemplified used real data from a chosen wind farm.

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We present a decadal-scale late Holocene climate record based on diatoms, biogenic silica, and grain size from a 12-m sediment core (VEC02A04) obtained from Frederick Sound in the Seymour-Belize Inlet Complex of British Columbia, Canada. Sediments are characterized by graded, massive, and laminated intervals. Laminated intervals are most common between c. 2948–2708 cal. yr BP and c. 1992–1727 cal. yr BP. Increased preservation of laminated sediments and diatom assemblage changes at this time suggest that cli- mate became moderately drier and cooler relative to the preceding and succeeding intervals. Spectral and wavelet analyses are used to test for statistically significant periodicities in time series of proxies of primary production (total diatom abundance, biogenic silica) and hydrology (grain size) preserved in the Frederick Sound record. Periodicities of c. 42–53, 60–70, 82–89, 241–243, and 380 yrs are present. Results are com- pared to reconstructed sunspot number data of Solanki et al. (2004) using cross wavelet transform to evalu- ate the role of solar forcing on NE Pacific climate. Significant common power of periodicities between c. 42– 60, 70–89, 241–243, and of 380 yrs occur, suggesting that celestial forcing impacted late Holocene climate at Frederick Sound. Replication of the c. 241–243 yr periodicity in sunspot time series is most pronounced be- tween c. 2900 cal. yr BP and c. 2000 cal. yr BP, broadly correlative to the timing of maximum preservation of laminated sedimentary successions and diatom assemblage changes. High solar activity at the Suess/de Vries band may have been manifested as a prolonged westward shift and/or weakening of the Aleutian Low in the mid-late Holocene, which would have diverted fewer North Pacific storms and resulted in the relatively dry conditions reconstructed for the Seymour-Belize Inlet Complex.