Ballistocardiography (BCG) has the interesting feature that no electrodes are needed to be attached to the body during measurements. this provides a potential application to assess a patient's heart condition in t...
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Ballistocardiography (BCG) has the interesting feature that no electrodes are needed to be attached to the body during measurements. this provides a potential application to assess a patient's heart condition in the home. Artificial neural networks (ANNs) have several properties that make them promising for automatic signal classification problems. In the time domain of the BCG classification, the whole cardiac cycle of BCG waveform needs a large-sized neural network which makes the classification a computationally intensive task. By classifying the data in a compressed format, savings in computer time may be realised. Here, the authors used wavelet multiresolution property analysis that allows one to obtain a significant information content from the BCG signal. small subsets of the wavelet coefficients were used to classify the normal, hypertension and heart attack risk patients by neural networks. It is shown that the proposed system achieved an overall 95.39% correct classification rate for the test data set. the classification of the features obtained by principal component analysis can only achieve a 92.8% overall performance. the advantage of the proposed classification system is that it can be easily implemented into a portable device.
this paper describes a highly adaptive video motion detection and tracking algorithm that has been developed as part of Sandia's Advanced Exterior Sensor (AES) program. the AES detection and tracking algorithm pro...
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this paper describes a highly adaptive video motion detection and tracking algorithm that has been developed as part of Sandia's Advanced Exterior Sensor (AES) program. the AES detection and tracking algorithm provides good performance under stressing data and environmental conditions. Features of the algorithm include the following: reliable detection with negligible false alarm rate of variable velocity targets having low signal-to-clutter ratios;reliable tracking of targetsthat show motion that is non-inertial;automatic adaptation to both infrared and visible imagery with variable quality;and suppression of false alarms caused by sensor flaws or cutouts, or both.
this paper describes a new architecture for performing data compression on a large matrix of parallel digital inputs, only a small proportion of which carries a logical T. the system assigns a unique address to each o...
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In real-time digital-signalprocessing systems, data often enter or leave the computationally intensive parts at small integer multiples of the clocking interval. In these cases, traditional microprocessor-based archi...
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Increasing attention is currently being given to the problem of an effective synchronization in live performance, between musicians and electronic synthesis system, in order to add a satisfactory degree of human sensi...
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Acoustic signal tracking is formulated as a simulated annealing problem. Detection of the track is based on a global optimization of a cost function which relates to the signal to noise ratio. the track can move only ...
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ISBN:
(纸本)0818621804
Acoustic signal tracking is formulated as a simulated annealing problem. Detection of the track is based on a global optimization of a cost function which relates to the signal to noise ratio. the track can move only 0, -1, or +1 position from time line to time line. the constraint is built into the next state generation of the algorithm. Emphasis is on the small scale localization of the track with known starting position. the procedure can detect -18 dB monotone data which is superior to any conventional technique. Dependency of equilibrium iterations with respect to S/N was revealed in the experimental results. this procedure is also tested with an inaccurate starting position in the image, and it yielded acceptable performance.
In the past there was a rapid development of new components for matched filtering of signals with large time-bandwidth-product on the basis of surface acoustic waves (SAW). Such components, as the SAW convolver, allow...
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In the past there was a rapid development of new components for matched filtering of signals with large time-bandwidth-product on the basis of surface acoustic waves (SAW). Such components, as the SAW convolver, allow the realization of fast and precise operating distance measurement systems with a minimum of components in the signalprocessing circuitry. In addition continous wave (CW) radar systems employ a minimum of radiation power. A microcomputer-controlled distance measurement system using a SAW convolver is presented. For data acquisition a special interface circuitry has been realized that allows real-time distance measurement of up to sixteen targets within the observed range. For an improvement of the range accuracy a combination of time-delay and phase measurement is employed.
In the past there was a rapid development of new components for matched filtering of signals with large time-bandwidth-product on the basis of surface acoustic waves (SAW). Such components, as there is the SAW-Convolv...
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In the past there was a rapid development of new components for matched filtering of signals with large time-bandwidth-product on the basis of surface acoustic waves (SAW). Such components, as there is the SAW-Convolver /1/, allow the realization of very fast and precise operating distance measurement systems with a minimum of components in the signalprocessing circuitry. In addition continous wave (CW) Radarsystems employ a minimum of radiation power /2/. In this paper a microcomputer-controlled distance measurement system using a SAW-Convolver is presented. For data acquisition a special interface circuitry has been realized that allows real-time distance measurement of up to sixteen targets within the observed range. For an improvement of the range accuracy a combination of time-delay and phase measurement is employed in this system.
Withthe commercial availability of high speed digital signal processors, it is now possible to implement all the linear predictive coding (LPC) tasks (excluding D-A/A-D conversion) on a single chip. In this paper, a ...
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Withthe commercial availability of high speed digital signal processors, it is now possible to implement all the linear predictive coding (LPC) tasks (excluding D-A/A-D conversion) on a single chip. In this paper, a very small, high quality, full-duplex, 10th order 2.4 kbps LPC vocoder is described. A single Texas Instruments TMS-320 microprocessor performs LPC analysis, pitch detection, synthesis, and data I/O. At the time of writing this paper, a total of 20 off-the-shelf integrated circuits were used occupying two thirds of a 14cm × 18cm wirewrap board (excluding power supply). the total power dissipation is less than 2 watts. the chip count may be reduced by a factor of two by combining the random logic on a semi-custom integrated circuit. When produced commercially, the cost of this vocoder should be considerably less than existing LPC units.
Image reconstruction from projections has been extensively studied in radioastronomy and medical imaging. the same techniques can be applied to multiple target detection tasks such as radar or sonar signalprocessing....
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Image reconstruction from projections has been extensively studied in radioastronomy and medical imaging. the same techniques can be applied to multiple target detection tasks such as radar or sonar signalprocessing. However, in medical imaging and radioastronomy, the images to be reconstructed are generally "compact" and the ratio between the required image size and resolution is small compared to that of the target detection problem where the images are sparse and fine resolution is required. therefore a larger number of basis functions will be necessary to discretize the general image. thus medical image reconstruction techniques applied directly to target detection can result in excessive memory requirements, computational time and required number of measurements. With modifications that consider the sparseness and positiveness of the images, reconstruction techniques have a potentially valuable application in the multiple target detection problem. In this paper we propose two modifications of the medical image reconstruction technique for the multi-target detection problem. One consists of pre-processingthe data in order to reduce the total image to a smaller set of regions likely to contain targets. the second consists of dividing the image into pixels much larger than the expected size of a target and estimating the total target intensity for each pixel.
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