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Unitary similarity transformations furnish a powerful vehicle for generating innnite generic classes of signal analysis and processing tools based on concepts diierent from time, frequency, and scale. Implementation of these new tools involves simply preprocessing the signal by a unitary transformation , performing standard processing techniques on the(More)
Time-frequency representations with fixed windows or kernels figure prominently in many applications, but perform well only for limited classes of signals. Representations with signal-dependent kernels can overcome this limitation. However, while they often perform well, most existing schemes are block-oriented techniques unsuitable for on-line(More)
This tutorial paper describes the methods for constructing fast algorithms for the computation of the discrete Fourier transform (DFT) of a real-valued series. The application of these ideas to all the major fast Fourier transform (FFT) algorithms is discussed, and the various algorithms are compared. We present a new implementation of the real-valued(More)
—The high peak-to-average power ratio (PAR) in Orthogonal Frequency Division Multiplexing (OFDM) modulation systems can significantly reduce power efficiency and performance. Methods exist which alter or introduce new signal constellations to combat large signal peaks. We present a new PAR-reduction method that dynamically extends outer constellation points(More)
—In the censoring approach to decentralized detection, sensors transmit real-valued functions of their observations when " informative " and save energy by not transmitting otherwise. We address several practical issues in the design of censoring sensor networks including the joint dependence of sensor decision rules, randomization of decision strategies,(More)
It has long been known that a fixed ordering of optimization phases will not produce the best code for every application. One approach for addressing this phase ordering problem is to use an evolutionary algorithm to search for a specific sequence of phases for each module or function. While such searches have been shown to produce more efficient code, the(More)
The reverberation time (RT) is an important parameter for characterizing the quality of an auditory space. Sounds in reverberant environments are subject to coloration. This affects speech intelligibility and sound localization. Many state-of-the-art audio signal processing algorithms, for example in hearing-aids and telephony, are expected to have the(More)
Signal-dependent time-frequency representations, by adapting their functional form to t the signal being analyzed, ooer many performance advantages over conventional representations. In this paper, we propose a simple, eecient technique for continuously adapting time-frequency representations over time. The procedure computes a short-time quality measure of(More)
A time-frequency representation based on an optimal , signal-dependent kernel has been proposed recently in an attempt to overcome one of the primary limitations of bilinear time-frequency distributions: that the best kernel and distribution depend on the signal to be analyzed. The optimization formulation for the signal-dependent kernel results in a linear(More)