Amin et. al. recently developed a time-frequency MUSIC algorithm with narrow band models for the estimation of direction of arrival (DOA) when the source signals are chirps. In this research, we consider wideband mode...
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Amin et. al. recently developed a time-frequency MUSIC algorithm with narrow band models for the estimation of direction of arrival (DOA) when the source signals are chirps. In this research, we consider wideband models. The joint time-frequency analysis is first used to estimate the chirp rates of the source signals and then the DOA is estimated by the MUSIC algorithm with an iterative approach.
Scale as a physical quantity is a recently developed concept. The scale transform can be viewed as a special case of the more general Mellin transform and its mathematical properties are very applicable in the analysi...
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Scale as a physical quantity is a recently developed concept. The scale transform can be viewed as a special case of the more general Mellin transform and its mathematical properties are very applicable in the analysis and interpretation of the signals subject to scale changes. A number of single-dimensional applications of scale concept have been made in speech analysis, processing of biological signals, machine vibration analysis and other areas. Recently, the scale transform was also applied in multi-dimensional signalprocessing and used for image filtering and denoising. Discrete implementation of the scale transform can be carried out using logarithmic sampling and the well-known fast Fourier transform. Nevertheless, in the case of the uniformly sampled signals, this implementation involves resampling. An algorithm not involving resampling of the uniformly sampled signals has been derived too. In this paper, a modification of the later algorithm for discrete implementation of the direct scale transform is presented. In addition, similar concept was used to improve a recently introduced discrete implementation of the inverse scale transform. Estimation of the absolute discretisation errors showed that the modified algorithms have a desirable property of yielding a smaller region of possible error magnitudes. Experimental results are obtained using artificial signals as well as signals evoked from the temporomandibular joint. In addition, discrete implementations for the separable two-dimensional direct and inverse scale transforms are derived. Experiments with image restoration and scaling through two-dimensional scale domain using the novel implementation of the separable two-dimensional scale transform pair are presented.
The ULV decomposition (ULVD) is an important member of a class of rank-revealing two-sided orthogonal decompositions used to approximate the singular value decomposition (SVD). The ULVD can be updated and downdated mu...
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The ULV decomposition (ULVD) is an important member of a class of rank-revealing two-sided orthogonal decompositions used to approximate the singular value decomposition (SVD). The ULVD can be updated and downdated much faster than the SVD, hence its utility in the solution of recursive total least squares (TLS) problems. However, the robust implementation of ULVD after the addition and deletion of rows (called updating and downdating respectively) is not altogether straightforward. When updating or downdating the ULVD, the accurate computation of the subspaces necessary to solve the TLS problem is of great importance. In this paper, algorithms are given to compute simple parameters that can often show when good subspaces have been computed.
A digital audio watermarking scheme of low complexity is proposed in this research as an effective way to deter users from misusing or illegally distributing audio data. Previous work on audio watermarking has primari...
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A digital audio watermarking scheme of low complexity is proposed in this research as an effective way to deter users from misusing or illegally distributing audio data. Previous work on audio watermarking has primarily focused on the inaudibility of the embedded watermark and its robustness against attacks such as compression and noise. In this research, special attention is paid to the synchronization attack caused by casual audio editing or malicious random cropping, which is a low-cost yet effective attack to watermarking algorithms developed before. The proposed scheme is based on audio content analysis and watermark embedding in the Fourier transform domain. A blind watermark detection technique is developed to identify the embedded watermark under various types of attacks.
This paper studies an approach to solve the problem of color purification for images of scanned paper maps in an experimental manner. The mathematical foundation of the approach is briefly outlined. A computationally ...
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This paper studies an approach to solve the problem of color purification for images of scanned paper maps in an experimental manner. The mathematical foundation of the approach is briefly outlined. A computationally feasible algorithm is then proposed. This algorithm is tested through real life testing. Results indicate that this approach not only restores and purifies colors of the map digitally. It compresses the data of the image files too.
Originally coined by the sensory psychologist Roger Shepard in the 1960's, chroma transforms frequency into octave equivalence classes. By extending the concept of chroma to chroma strength and how it varies over ...
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Originally coined by the sensory psychologist Roger Shepard in the 1960's, chroma transforms frequency into octave equivalence classes. By extending the concept of chroma to chroma strength and how it varies over time, we have demonstrated the utility of chroma in simplifying the processing and representation of signals dominated by harmonically-related narrowband components. These investigations have utilized an ad hoc procedure for calculating the chromagram from a given time-frequency distribution. The present paper is intended to put this ad hoc procedure on more sound mathematical ground.
Subband-domain algorithms provide an attractive technique for wideband radar array processing. The subband-domain approach decomposes a received wideband signal into a set of narrowband signals. While the number of pr...
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Subband-domain algorithms provide an attractive technique for wideband radar array processing. The subband-domain approach decomposes a received wideband signal into a set of narrowband signals. While the number of processing threads in the system increases, the narrowband signals within each subband can be sampled at a correspondingly slower rate. Therefore, the data rate at the input is similar to that at the output of the subband processor. There are several advantages to the subbanding method. It can simplify typical radar algorithms such as adaptive beamforming and equalization by the virtue of reducing subband signal bandwidth, thereby potentially reducing the computational complexity over an equivalent tapped-delay line approach. It also allows for a greater parallelization of the processing task, hence enabling the use of slower and less power consuming hardware. In order to evaluate the validity of the subbanding approach, it is compared with conventional processing methods. This paper focuses on adaptive beamforming and pulse compression performance for a wideband radar system. The performance of an adaptive beamformer is given for a polyphase filter based subband approach and is measured against narrowband processing. SINR loss curves and beampatterns for a subband system are presented. Design criteria for subband polyphase filter processing that minimizes signal distortion are provided and the distortion is characterized. Finally subband-domain pulse compression is demonstrated and compared with the conventional approach.
As with the case of instantaneous frequency, it is often difficult to interpret the instantaneous bandwidth of most signals: both quantities typically range beyond the spectral support of the signal, yielding the para...
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As with the case of instantaneous frequency, it is often difficult to interpret the instantaneous bandwidth of most signals: both quantities typically range beyond the spectral support of the signal, yielding the paradox that the instantaneous bandwidth (and frequency) can be greater than the global bandwidth of the signal. A new definition of instantaneous frequency that does not suffer from this difficulty has recently been given, and we build on those results here to obtain a new definition of instantaneous bandwidth. Kernel constraints for a Cohen-class time-frequency distribution to yield these new results for its conditional moments are also given.
We present a discussion of methods based on the complex cross-spectrum and the application of these methods to the analysis of speech. The cross spectral methods developed here are an extension of methods developed in...
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We present a discussion of methods based on the complex cross-spectrum and the application of these methods to the analysis of speech. The cross spectral methods developed here are an extension of methods developed in the 1980's by one of the authors for accurately estimating stationary and cyclo-stationary parameters of signals buried deep in the noise. Since speech is non-stationary and therefore supports very little integration, the methods have been re-developed to address issues such as non-stationarity, harmonic structures and rapidly changing resonance Cross-spectral methods are presented as complex valued time-frequency surface methods which provide signal parameter estimation by taking advantage of signal structure. These methods have proven to be very powerful.
The performances of high-resolution array processing methods are known to degrade in random inhomogeneous media because the amplitude and phase of each wavefront tend to fluctuate and to loose their coherence between ...
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The performances of high-resolution array processing methods are known to degrade in random inhomogeneous media because the amplitude and phase of each wavefront tend to fluctuate and to loose their coherence between array sensors. As a result, in the presence of such a multiplicative noise, the conventional coherent wavefront model becomes inapplicable. Such a type of degradation may be especially strong for large aperture arrays. Below, we develop new high-resolution covariance matching (CM) techniques with an improved robustness against multiplicative noise and related coherence losses. Using a few unrestrictive physics-based assumptions on the environment, we show that reliable algorithms can be developed which take into account possible coherence losses. Computer simulation results and real sonar data processing results are presented. These results demonstrate drastic improvements achieved by our approach as compared with conventional high-resolution array processing techniques.
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