A recursive ray acoustics (RRA) algorithm for three-dimensional speeds of sound is presented. The RRA algorithm is simple, fast, and accurate and uses arc length as the independent variable. In its present form, it ca...
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A recursive ray acoustics (RRA) algorithm for three-dimensional speeds of sound is presented. The RRA algorithm is simple, fast, and accurate and uses arc length as the independent variable. In its present form, it can be used to compute the position, angles of propagation, travel time, and path length along a ray path. Preliminary results from computer simulation studies designed to test the algorithm's accuracy and capabilities are also presented.
A video decoder with an efficient block-level-pipeline controller scheme for MPEG-2 MP@ML is presented in this paper. The architecture in most of the reported literature for MPEG-2 MP@ML video uses a 64-bit bus and a ...
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A video decoder with an efficient block-level-pipeline controller scheme for MPEG-2 MP@ML is presented in this paper. The architecture in most of the reported literature for MPEG-2 MP@ML video uses a 64-bit bus and a complex bus arbitration scheme to communicate with external DRAM, display, and incoming FIFO. Our design imposes a certain order in the DRAM access by various processing units instead of allowing any processing unit within the decoder to request bus access arbitrarily. This efficient DRAM accessing order allows us to reduce bus width from 64 bits to 32 bits, without significantly increasing embedded buffer sizes, and still meet the requirements for MPEG-2 MP@ML real-time decoding. The bus arbitration algorithm is also simple, allowing for a less complex controller design.
An algorithm for computing the aspect graph for polyhedral objects is described. The aspects graph is a representation of three-dimensional objects by a set of two-dimensional views. The set of viewpoints on the Gauss...
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An algorithm for computing the aspect graph for polyhedral objects is described. The aspects graph is a representation of three-dimensional objects by a set of two-dimensional views. The set of viewpoints on the Gaussian sphere is partitioned into regions such that in each region the qualitative structure of the line drawing remains the same. At the boundaries between adjacent regions are the accidental viewpoints where the structure for the line drawing changes. It is shown that for polyhedral objects there are two fundamental visual events: (1) the projections of an edge and a vertex coincide; and (2) the projections of three nonadjacent edges intersect at a point. The geometry of the object is reflected in the locus of the accidental viewpoints. The algorithm computes the partition together with a representative view for each region of the partition.
Since its publication by the Educational Testing Service in 1962, the MBTI (Myers-Briggs-Type Indicator) has seen application in a variety of settings. Its usefulness to the classroom teacher, however, is unclear at t...
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Since its publication by the Educational Testing Service in 1962, the MBTI (Myers-Briggs-Type Indicator) has seen application in a variety of settings. Its usefulness to the classroom teacher, however, is unclear at this time. This investigation addressed the relationship of two dimensions of that instrument, Sensing-Intuiting (S-N) and Judging-Perceiving (J-P), to performance on tests containing both computational problems and multiple choice questions. The objective of the investigation was to determine whether particular types of testing offer an advantage to certain individuals due to their preferred ways of internalizing and processing information. Tests in a sophomore-level strength of materials course were constructed to contain several computational problems and 10 multiple choice questions each. Questions were designed to operate at one of three levels of the problem-solving taxonomy: diagnosis, routines or interpretation. The performances of both S-N students and J-P students were compared on both problems and multiple choice questions within each test and on the departmental final examination. No differences due to the J-P dimension were detected. The S-N dimension, however, yielded several significant differences. N-type students performed substantially better on multiple choice questions on two of the three examinations given and better on computational problems on one of the three examinations. As expected, they excelled on those questions which tested at the ``interpretation'' level. No differences were seen on questions requiring diagnosis or routines. In all cases, even when differences did not achieve significance, there was a trend favoring the N-type student.
作者:
MACINNES, CIBM CORP
DIV GEN TECHNOLE FISHKILL FACILHOPEWELL JUNCTIONNY 12533
In the analysis of large electrical circuits, encompassing thousands of nodes and circuit elements, sparse matrix techniques are essential to the efficient solution of the resulting sparse linear systems. The maintena...
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In the analysis of large electrical circuits, encompassing thousands of nodes and circuit elements, sparse matrix techniques are essential to the efficient solution of the resulting sparse linear systems. The maintenance of sparsity during Gaussian elimination is of paramount importance. In an attempt to preserve sparsity during Gaussian elimination, circuit analysis programs such as ASTAP [1] and AS/X [9] permute rows and columns of the circuit matrix using the Markowitz reordering technique [4];this is done prior to the execution of the analysisalgorithm. Since row and/or column pivoting during the analysis would tend to destroy the initial sparsity-preserving arrangement of rows and columns, this is not allowed at, possibly, the expense of solution accuracy. A technique, termed small pivot perturbation (SPP), is presented which can improved the accuracy of Gaussian elimination in those cases where small pivot magnitudes are encountered during the Gaussian elimination procedure, thus avoiding an inaccurate solution and allowing the analysis to continue. The SPP technique is applicable to either time-domain or frequency-domain analysis and is especially useful with circuit equation formulations where "perfect cancellation" can occur during Gaussian elimination, such as in some implementations of the modified nodal formulation [2], [3].
In this paper, some new qualitative properties of discrete-time neural networks based on the ''brain-state-in-a-box'' model are presented. These properties concern both the characterization of equilibr...
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In this paper, some new qualitative properties of discrete-time neural networks based on the ''brain-state-in-a-box'' model are presented. These properties concern both the characterization of equilibrium points and the global dynamical behavior, Next, the analysis results are used as guidelines in developing an efficient synthesis procedure for networks that function as associative memories, A constrained designalgorithm is presented that gives completely stable dynamical neural networks sharing some interesting features. It is guaranteed the absence of nonbinary stable equilibria, that is stable states with nonsaturated components, It is guaranteed that in close proximity (Hamming distance one) of the stored patterns there is no other binary equilibrium point, Moreover, the presented method allows one to optimize a design parameter that controls the size of the attraction basins of the stored vectors and the accuracy needed in a digital realization of the network, Some design examples and computer simulations are presented to demonstrate the effectiveness of the proposed method.
Using the framework of cyclic-service systems with a single server, two different token-passing models are investigated. The first model is approximate, obtaining the free-tokens cycle-time distribution on an asymmetr...
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Using the framework of cyclic-service systems with a single server, two different token-passing models are investigated. The first model is approximate, obtaining the free-tokens cycle-time distribution on an asymmetric system with infinite capacity buffers and single-token operation. The second model is exact, yielding the cycle-time distribution of the free token on an asymmetric system with unit-capacity buffers, and single-token operation. The latter result is verified using known results for symmetric, unit-capacity buffer systems. To demonstrate the positive effects of buffering, a small variation of the unit-capacity buffering scheme is introduced. Computational results include performance measures such as throughput, utilization, loss probabilities, mean cycle times, cycle-time distributions, and a comparison of two buffering schemes
This paper describes a new method of data reduction and classification in a multidimensional symptom space for diagnostic aid of congenital heart diseases. The algorithm developed here is to reduce interactively a mul...
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This paper describes a new method of data reduction and classification in a multidimensional symptom space for diagnostic aid of congenital heart diseases. The algorithm developed here is to reduce interactively a multidimensional symptom space to sectorial regions representing each disease in a semicircle using the modified constellation graph method. This method enables us to classify patients using the angle in the semicircle as a single classifying parameter with an accuracy of about 90%, that is, with little overlapping between disease sectors. Comparing this method with conventional factor analysis, we have found the former far more effective than the latter for disease region separation.
The applications of multivariate Edgeworth series and higher-order statistics to the discrete-time detection of a known constant signal in multivariate non-Gaussian noise are considered. A technique to derive suboptim...
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The applications of multivariate Edgeworth series and higher-order statistics to the discrete-time detection of a known constant signal in multivariate non-Gaussian noise are considered. A technique to derive suboptimum detectors from the Neyman-Pearson optimum and locally optimum detectors is described. A numerical algorithm based on knowledge of the noise cumulants is presented in order to analyze the finite-sample size performance of the suboptimum detectors. As an example, the performance of the detectors as compared with the linear detector in multivariate Gaussian-Gaussian mixture noise is presented via receiver operating characteristic curves. Numerical results indicate that the suboptimum detectors, when exploiting knowledge of the dependence structure of the noise, can have very good performance with respect to the linear detector.
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