Using singular value distribution (SVD) of backscattered impulse response matrix to differentiate between low and high porosity in cortical bone

2019 ◽  
Vol 146 (4) ◽  
pp. 2942-2942
Author(s):  
Omid Yousefian ◽  
Yasamin Karbalaeisadegh ◽  
Marie M. Muller
Keyword(s):  
Cortical Bone ◽  
Impulse Response ◽  
Singular Value ◽  
Value Distribution ◽  
High Porosity ◽  
Response Matrix

A minimal canonical realization algorithm for impulse response matrix using moments

1975 ◽  
Vol 63 (3) ◽  
pp. 538-540 ◽  
Author(s):  
M. Lal ◽  
H. Singh ◽  
R. Parthasarathy
Keyword(s):  
Impulse Response ◽  
Response Matrix ◽  
Canonical Realization

On the realization of a class of time varying impulse response matrix

1977 ◽  
Vol 65 (7) ◽  
pp. 1064-1065 ◽  
Author(s):  
J.S. Bedi ◽  
H. Singh ◽  
A.K. Kamal
Keyword(s):  
Impulse Response ◽  
Time Varying ◽  
Response Matrix

scholarly journals Load Localization and Reconstruction Using a Variable Separation Method

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Jing Zhang ◽  
Fang Zhang ◽  
Jinhui Jiang
Keyword(s):  
Impulse Response ◽  
Time History ◽  
Separation Method ◽  
Location Information ◽  
Engineering Practice ◽  
Variable Separation ◽  
Response Matrix ◽  
Optimization Function ◽  
Load Location ◽  
Variable Separation Method

Load identification is very important in engineering practice. In this paper, a novel method for load reconstruction and localization is proposed. In the traditional load localization method, location information is coupled to the impulse response matrix. The inversion of the impulse response matrix leads the process of load localization to be time-consuming. So we propose a variable separation method to separate the load location information from the impulse response matrix. An error optimization function of load histories in different modes is employed to determine the true load location. After locating the external load, the load time history can be easily reconstructed by the measurement responses and determinate impulse response matrix. This method is verified by simulations of a simply supported beam acted by a sine load and an impact separately. An experiment is also carried out to validate the feasibility and accuracy of the proposed method.

scholarly journals On temporal codes and the spatiotemporal response of neurons in the lateral geniculate nucleus

1994 ◽  
Vol 72 (6) ◽  
pp. 2990-3003 ◽  
Author(s):  
D. Golomb ◽  
D. Kleinfeld ◽  
R. C. Reid ◽  
R. M. Shapley ◽  
B. I. Shraiman
Keyword(s):  
Singular Value Decomposition ◽  
Firing Rate ◽  
Impulse Response ◽  
Linear Response ◽  
Impulse Response Function ◽  
Singular Value ◽  
Temporal Coding ◽  
Temporal Mode ◽  
Temporal Modes ◽  
Value Decomposition

1. The present work relates recent experimental studies of the temporal coding of visual stimuli (McClurkin, Optican, Richmond, and Gawne, Science 253: 675, 1991) to the measurements of the spatiotemporal receptive fields of neurons within the lateral geniculate of primate. 2. We analyze both new and previously described magnocellular and parvocellular single units. The spatiotemporal impulse response function of the unit, defined as the time-resolved average firing rate in response to a weak stimulus flashed at a given location and time, is characterized by the singular value decomposition. This analysis allows one to represent the impulse response by a small number, two to three, of spatial and temporal modes. Both magnocellular and parvocellular units are weakly nonseparable, with major and minor modes that account, respectively, for approximately 78 and 22% of the response. The major temporal mode for both types is essentially identical for the first 100 ms. At later times the response of magnocellular units changes sign and decays slowly, whereas the response of parvocellular units decays relatively rapidly. 3. The spatiotemporal impulse response function completely determines the response of a unit to an arbitrary stimulus when linear response theory is valid. Using the measured impulse response, combined with a rectifying neuronal input-output relation, we calculate the responses to a complete set of spatial luminance patterns constructed of "Walsh" functions. Our predicted temporal responses are in qualitative agreement with those reported for parvocellular units (McClurkin, Optican, Richmond, and Gawne, J. Neurophysiol. 66: 794, 1991). Under the additional assumptions of Poisson statistics for the probability of spiking and a plausible background firing rate, we predict the performance of a unit in the Walsh pattern discrimination task as quantified by mutual information. Our prediction is again consistent with the reported results. 4. Last, we consider the issue of temporal coding within linear response. For stimuli presented for fixed time intervals, the singular value decomposition provides a natural relation between the temporal modes of the neuronal response and the spatial pattern of the stimulus. Although it is tempting to interpret each temporal mode as an independent channel that encodes orthogonal features of the stimulus, successively higher order modes are increasingly unreliable and do not significantly increase the discrimination capabilities of the unit.

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