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Titlebook: Wavelets; Time-Frequency Metho Jean-Michel Combes,Alexander Grossmann,Philippe Tc Conference proceedings 1990Latest edition Springer-Verlag

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51#
發(fā)表于 2025-3-30 11:36:09 | 只看該作者
Coherence and Projectors in AcousticsA general method to decompose a stationary random sound field in the frequency domain is presented. This method is based on a geometrical interpretation of the partial coherence theory proposed by Dodds[1] and can be applied to the fundamental study of sound sources and fields in the low frequency domain [2][3].
52#
發(fā)表于 2025-3-30 13:04:45 | 只看該作者
Coherence and Projectors in AcousticsA general method to decompose a stationary random sound field in the frequency domain is presented. This method is based on a geometrical interpretation of the partial coherence theory proposed by Dodds[1] and can be applied to the fundamental study of sound sources and fields in the low frequency domain [2][3].
53#
發(fā)表于 2025-3-30 17:29:58 | 只看該作者
Some Aspects of Non-Stationary Signal Processing with Emphasis on Time-Frequency and Time-Scale Methale versions which implicitly make use of “wavelet” concepts. Relationships between Gabor expansion, wavelet transform and ambiguity functions are detailed by considering signal decomposition as a detection-estimation problem. This permits one to make more precise some of the links which exist between time-frequency and time-scale.
54#
發(fā)表于 2025-3-30 20:52:12 | 只看該作者
55#
發(fā)表于 2025-3-31 02:37:35 | 只看該作者
Detection of Abrupt Changes in Signal Processingodels where abrupt changes -or discontinuities- in (some of) the parameters may occur and between which the signal characteristics are to be considered as constant or slowly varying. The main problem is to detect the changes and to estimate their location (time or space) and magnitude.
56#
發(fā)表于 2025-3-31 05:47:40 | 只看該作者
Detection of Abrupt Changes in Signal Processingodels where abrupt changes -or discontinuities- in (some of) the parameters may occur and between which the signal characteristics are to be considered as constant or slowly varying. The main problem is to detect the changes and to estimate their location (time or space) and magnitude.
57#
發(fā)表于 2025-3-31 09:19:25 | 只看該作者
58#
發(fā)表于 2025-3-31 14:05:42 | 只看該作者
Wavelet Transformations in Signal Detectionof cycles. The analyzing wavelets must satisfy a few simple conditions, but are not otherwise specified. There is therefore a wide latitude in the choice of these functions and they can be taylored to specific applications. We have applied them to detect ventricular delayed potentials (VLP) in the el echocardiogram.
59#
發(fā)表于 2025-3-31 20:34:51 | 只看該作者
Wavelets and Granular Analysis of Speechnformation in the signal is mainly related to the evolution of the two or three first resonances of the vocal tract, called “formants” F1, F2, F3. The vocal cords vibrating frequency, Fo, is closely related to a perceptive quality of sounds called “pitch”.
60#
發(fā)表于 2025-3-31 23:27:16 | 只看該作者
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