The Experts below are selected from a list of 291 Experts worldwide ranked by ideXlab platform
Yoriyuki Yamagata - One of the best experts on this subject based on the ideXlab platform.
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strong normalization of the second order symmetric λμ calculus
Information & Computation, 2004Co-Authors: Yoriyuki YamagataAbstract:Parigot [Computational Logic and Proof Theory, vol. 713, 1993, p. 263] suggested symmetric structural reduction rules to ensure Unique Representation of data types. We prove strong normalization of the second-order λµ-calculus with such rules.
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strong normalization of second order symmetric lambda mu calculus
International Symposium on Theoretical Aspects of Computer Software, 2001Co-Authors: Yoriyuki YamagataAbstract:Parigot suggested symmetric structural reduction rules for application to µ-abstraction in [9]to ensure Unique Representation of data type. We prove strong normalization of second order ?µ-calculus with these rules.
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TACS - Strong Normalization of Second Order Symmetric Lambda-mu Calculus
Lecture Notes in Computer Science, 2001Co-Authors: Yoriyuki YamagataAbstract:Parigot suggested symmetric structural reduction rules for application to µ-abstraction in [9]to ensure Unique Representation of data type. We prove strong normalization of second order ?µ-calculus with these rules.
Roger M Enoka - One of the best experts on this subject based on the ideXlab platform.
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detecting the Unique Representation of motor unit action potentials in the surface electromyogram
Journal of Neurophysiology, 2008Co-Authors: Dario Farina, Francesco Negro, Marco Gazzoni, Roger M EnokaAbstract:This study investigated the relative proportion of motor-unit action potentials that are Uniquely represented in the simulated and experimental surface electromyogram (EMG). Two hundred motor units were simulated in a cylindrical anatomical system. Action potentials for each motor unit were generated with a model and then compared with those of other motor units. Pairs of motor units were considered indistinguishable and the motor units not Uniquely represented in the surface EMG, when the difference in the mean energy for the pair of potentials was <5%. The anatomical conditions and recording configurations had a substantial influence on the percentage of motor units that could be Uniquely identified in the simulated EMG. For example, a single monopolar channel could discriminate only 3.4% of motor units in the simulated population, whereas a system with 81 Laplacian channels arranged in a grid could discriminate 83.8% of the motor units under the same conditions. The simulation results were confirmed with populations of motor units recorded experimentally from the abductor digiti minimi muscle of eight healthy men. Furthermore, the relative proportion of Uniquely identified motor units in the simulated signal was only moderately related to motor-unit size and distance from the electrodes. These results indicate the upper limit for detection of individual motor units from the surface EMG and show that a few channels of surface EMG recordings are not sufficient to study single motor units. The noninvasive identification of motor units from the surface EMG requires the use of multiple channels of information.
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Detecting the Unique Representation of motor-unit action potentials in the surface electromyogram.
Journal of Neurophysiology, 2008Co-Authors: Dario Farina, Francesco Negro, Marco Gazzoni, Roger M EnokaAbstract:This study investigated the relative proportion of motor-unit action potentials that are Uniquely represented in the simulated and experimental surface electromyogram (EMG). Two hundred motor units were simulated in a cylindrical anatomical system. Action potentials for each motor unit were generated with a model and then compared with those of other motor units. Pairs of motor units were considered indistinguishable and the motor units not Uniquely represented in the surface EMG, when the difference in the mean energy for the pair of potentials was
M. Sarfraz - One of the best experts on this subject based on the ideXlab platform.
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Visualization of Positive Data by Rational Cubic Spline Interpolant
2010 14th International Conference Information Visualisation, 2010Co-Authors: M. Sarfraz, Malik Zawwar Hussain, Tahira Sumbal ShaikhAbstract:This paper discusses the problem of constructing positive cubic spline interpolation. To obtain smooth curve for positive data, piecewise rational cubic function has been used. In the description of rational interpolant, two families of parameters have been constrained to preserve positive shape of the data, the rational spline scheme has a Unique Representation. In addition, to preserve the shape of positive data sets, the degree of smoothness attained is C2.
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Data visualization using rational spline interpolation
Journal of Computational and Applied Mathematics, 2006Co-Authors: M. Sarfraz, Malik Zawwar HussainAbstract:A smooth curve interpolation scheme for positive, monotonic, and convex data has been developed. This scheme uses piecewise rational cubic functions. The two families of parameters, in the description of the rational interpolant, have been constrained to preserve the shape of the data. The rational spline scheme has a Unique Representation. The degree of smoothness attained is C^1.
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A rational cubic spline for the visualization of monotonic data
Computers & Graphics, 2000Co-Authors: M. SarfrazAbstract:Abstract A smooth curve interpolation scheme for monotonic data has been developed. This scheme uses piecewise rational cubic functions. The two families of parameters, in the description of the rational interpolant, have been constrained to preserve the shape of the data. The rational spline scheme has a Unique Representation. The degree of smoothness attained is C2 which is more powerful than a previous C1 method.
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A smooth rational spline for visualizing monotone data
1999 IEEE International Conference on Information Visualization (Cat. No. PR00210), 1999Co-Authors: M. SarfrazAbstract:A C/sup 2/ curve interpolation scheme for monotonic data has been developed. This scheme uses piecewise rational cubic functions. The two families of parameters, in the description of the rational interpolant, have been constrained to preserve the shape of the data. The monotone rational cubic spline scheme has a Unique Representation.
Min Tang - One of the best experts on this subject based on the ideXlab platform.
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Unique Representation bi basis for rational numbers field
Periodica Mathematica Hungarica, 2017Co-Authors: Min TangAbstract:For \(A\subseteq {\mathbb {Q}}\), \(\alpha \in {\mathbb {Q}}\), let \(r_{A}(\alpha )=\#\{(a_{1}, a_{2})\in A^{2}: \alpha =a_{1}+a_{2}, a_{1}\le a_{2}\},\)\(\delta _{A}(\alpha )=\#\{(a_{1}, a_{2})\in A^{2}: \alpha =a_{1}-a_{2} \}.\) In this paper, we construct a set \(A\subset {\mathbb {Q}}\) such that \(r_{A}(\alpha )=1\) for all \(\alpha \in {\mathbb {Q}}\) and \(\delta _{A}(\alpha )=1\) for all \(\alpha \in {\mathbb {Q}}\setminus \{{0}\}\).
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A Unique Representation bi-basis for the integers. II
Bulletin of The Australian Mathematical Society, 2016Co-Authors: Min TangAbstract:For$n\in \mathbb{Z}$and$A\subseteq \mathbb{Z}$, define$r_{A}(n)$and${\it\delta}_{A}(n)$by$r_{A}(n)=\#\{(a_{1},a_{2})\in A^{2}:n=a_{1}+a_{2},a_{1}\leq a_{2}\}$and${\it\delta}_{A}(n)=\#\{(a_{1},a_{2})\in A^{2}:n=a_{1}-a_{2}\}$. We call$A$a Unique Representation bi-basis if$r_{A}(n)=1$for all$n\in \mathbb{Z}$and${\it\delta}_{A}(n)=1$for all$n\in \mathbb{Z}\setminus \{0\}$. In this paper, we prove that there exists a Unique Representation bi-basis$A$such that$\limsup _{x\rightarrow \infty }A(-x,x)/\sqrt{x}\geq 1/\sqrt{2}$.
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Unique Representation bi basis for the integers
Bulletin of The Australian Mathematical Society, 2014Co-Authors: Ran Xiong, Min TangAbstract:For \(n\in\mathbb{Z}\) and \(A\subseteq\mathbb{Z},\) let \(r_{A}(n)=\# \{(a_{1}, a_{2})\in A^{2}: n=a_{1}+a_{2}, a_{1}\leq a_{2}\}\) and \(\delta_{A}(n)=\# \{(a_{1}, a_{2})\in A^{2}: n=a_{1}-a_{2} \}.\) We call \(A\) a Unique Representation bi-basis if \(r_{A}(n)=1\) for all \(n\in\mathbb{Z}\) and \(\delta_{A}(n)=1\) for all \(n\in\mathbb{Z}\setminus\{0\}.\) In this paper, we construct a Unique Representation bi-basis of \(\mathbb{Z}\) whose growth is logarithmic. DOI: 10.1017/S0004972713000762
Dario Farina - One of the best experts on this subject based on the ideXlab platform.
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detecting the Unique Representation of motor unit action potentials in the surface electromyogram
Journal of Neurophysiology, 2008Co-Authors: Dario Farina, Francesco Negro, Marco Gazzoni, Roger M EnokaAbstract:This study investigated the relative proportion of motor-unit action potentials that are Uniquely represented in the simulated and experimental surface electromyogram (EMG). Two hundred motor units were simulated in a cylindrical anatomical system. Action potentials for each motor unit were generated with a model and then compared with those of other motor units. Pairs of motor units were considered indistinguishable and the motor units not Uniquely represented in the surface EMG, when the difference in the mean energy for the pair of potentials was <5%. The anatomical conditions and recording configurations had a substantial influence on the percentage of motor units that could be Uniquely identified in the simulated EMG. For example, a single monopolar channel could discriminate only 3.4% of motor units in the simulated population, whereas a system with 81 Laplacian channels arranged in a grid could discriminate 83.8% of the motor units under the same conditions. The simulation results were confirmed with populations of motor units recorded experimentally from the abductor digiti minimi muscle of eight healthy men. Furthermore, the relative proportion of Uniquely identified motor units in the simulated signal was only moderately related to motor-unit size and distance from the electrodes. These results indicate the upper limit for detection of individual motor units from the surface EMG and show that a few channels of surface EMG recordings are not sufficient to study single motor units. The noninvasive identification of motor units from the surface EMG requires the use of multiple channels of information.
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Detecting the Unique Representation of motor-unit action potentials in the surface electromyogram.
Journal of Neurophysiology, 2008Co-Authors: Dario Farina, Francesco Negro, Marco Gazzoni, Roger M EnokaAbstract:This study investigated the relative proportion of motor-unit action potentials that are Uniquely represented in the simulated and experimental surface electromyogram (EMG). Two hundred motor units were simulated in a cylindrical anatomical system. Action potentials for each motor unit were generated with a model and then compared with those of other motor units. Pairs of motor units were considered indistinguishable and the motor units not Uniquely represented in the surface EMG, when the difference in the mean energy for the pair of potentials was
