By expressing the frequency response of a Nyquist filter as a convolution of two functions, the mathematical complexity required to find the impulse response of the filter is reduced. Moreover, more efficient Nyquist ...
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By expressing the frequency response of a Nyquist filter as a convolution of two functions, the mathematical complexity required to find the impulse response of the filter is reduced. Moreover, more efficient Nyquist filters than the popular Raised Cosine filter (i.e. wider 3 dB bandwidth, same absolute bandwidth, and shorter or same length impulse response) are generated by using well known Window functions such as Ramming and Blackman.
This paper describes a simulator for the Shiva multiprocessor system and the simulator construction methodology (SCM) used in its creation. The SCM, based on the active functional unit (AFU) construct, is a modern SCM...
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Image decomposition based on the discrete wavelet transform (DWT) has been proposed for efficient storage and progressive transmission of images for visual browsing in digital image libraries. Although the compression...
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Image decomposition based on the discrete wavelet transform (DWT) has been proposed for efficient storage and progressive transmission of images for visual browsing in digital image libraries. Although the compression aspects of the DWT have been carefully researched, reconstruction errors due to corrupted wavelet coefficients have received less attention. In this paper we consider the problem of bit errors affecting uniformly quantized wavelet coefficients. The proposed method, which is based on a local image model, simultaneously detects and masks corrupted wavelet coefficients.
The delta operator approach to continuous-time cellular neural networks (CT-CNNs) is investigated in terms of a robust realization. It is shown that earlier results concerning the robustness of CT-CNNs can be obtained...
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The delta operator approach to continuous-time cellular neural networks (CT-CNNs) is investigated in terms of a robust realization. It is shown that earlier results concerning the robustness of CT-CNNs can be obtained as a limiting case of this approach, while at the same time, this allows us to formulate robustness considerations for discrete-time CNNs.
In this paper, a contrast pyramid based image coding method is described in which a simple nonlinear difference operation is introduced to generate residual information between two contiguous level images. The represe...
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In this paper, a contrast pyramid based image coding method is described in which a simple nonlinear difference operation is introduced to generate residual information between two contiguous level images. The representation of the residual information can be considered as a local contrast measure. As the difference image in established pyramid coding techniques, the contrast image has low variance, and data compression is achieved by quantizing the contrast image. Based on Weber's law and spatial masking of the human visual system, further data compression can be attained by selecting only perceptually significant information from the contrast image and coding it efficiently.
This paper describes a simulator for the Shiva multiprocessor system and the simulator construction methodology (SCM) used in its creation. The SCM, based on the active functional unit (AFU) construct, is a modern SCM...
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This paper describes a simulator for the Shiva multiprocessor system and the simulator construction methodology (SCM) used in its creation. The SCM, based on the active functional unit (AFU) construct, is a modern SCM which is flexible, accurate, fast, easy to use, capable of dynamic reconfigurability at run-time, and most of all simple and capable of quick simulator construction. The AFU SCM is capable of all these things through the use of object-oriented software techniques. The Shiva simulator constructed using the AFU SCM is program-driven and capable of micro and macro architectural simulation.
A new, robust and computationally attractive approach to the problem of time series classification is discussed in this paper. Both the Bayesian as well as a new adaptive classification scheme for source selection are...
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A new, robust and computationally attractive approach to the problem of time series classification is discussed in this paper. Both the Bayesian as well as a new adaptive classification scheme for source selection are discussed. Simulation results are included to demonstrate the effectiveness of the new methodology.
The detection of spatio-temporal scalp EEG patterns associated with voluntary motion preparation towards the development of a brain-computer interface (BCI) is explored. The rationale for the use of a spatio-temporal ...
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The detection of spatio-temporal scalp EEG patterns associated with voluntary motion preparation towards the development of a brain-computer interface (BCI) is explored. The rationale for the use of a spatio-temporal approach to this detection problem is explained. The need for a temporal or dynamic classifier is confirmed by demonstration of the lack of robustness in static neural network classifiers with respect to time alignment of the patterns under analysis. The results from dynamic classifiers, such as the Time Delay Neural Network (TDNN) and the Gamma Neural Network are presented in terms of their Receiver Operating Characteristic (ROC) Curves.
The existence of characteristic changes in the EEG of a subject preparing for the execution of a voluntary movement is reviewed. Some of those changes, i.e., the "readiness potentials" (RPs), are suggested a...
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The existence of characteristic changes in the EEG of a subject preparing for the execution of a voluntary movement is reviewed. Some of those changes, i.e., the "readiness potentials" (RPs), are suggested as a possible link between the internal processes associated with different forms of motion preparation and a digital signalprocessing system designed to classify the different intended movements. Such a system can potentially be used to provide input to a specialized graphic user interface, constituting a brain-computer interface (BCI). Our current work on neural-network classification of RPs is summarized and the results are presented.
Sipitca and Madisetti (see VCIP '96, Orlando, Florida, 1996) have proposed the use of analog position sensors for a more accurate motion compensation on videoconferencing sequences. We investigate the results of i...
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Sipitca and Madisetti (see VCIP '96, Orlando, Florida, 1996) have proposed the use of analog position sensors for a more accurate motion compensation on videoconferencing sequences. We investigate the results of including such a motion compensation scheme in a transform based encoder. The more successful motion compensation makes the resulting displaced frame difference (DFD) less correlated. In fact, the autocorrelation function goes practically to zero for a lag larger than 4-5 pels. Therefore, the 4/spl times/4 DCT can be used instead of the 8/spl times/8 DCT. This helps in dealing better with the relatively small regions where the DFD takes on larger values-on the border regions and in the new information regions. Finally, a block swapping algorithm and an appropriate error measure are introduced.
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