A 64x64 aer logarithmic temporal derivative silicon retina

2005 ◽  
Author(s):  
P. Lichtsteiner ◽  
T. Delbruck
Keyword(s):  
Silicon Retina ◽  
Temporal Derivative

On Calculation Schemes of Spatial Gradient for Spatio-temporal Derivative Method

2003 ◽  
Vol 23 (Supplement1) ◽  
pp. 21-24
Author(s):  
Yasufumi YAMAMOTO ◽  
Yuya AKAMATSU ◽  
Noriyoshi YONEHARA ◽  
Tomomasa UEMURA
Keyword(s):  
Spatial Gradient ◽  
Derivative Method ◽  
Temporal Derivative ◽  
Spatio Temporal

scholarly journals Lattice Boltzmann kinetic modeling and simulation of thermal liquid–vapor system

2014 ◽  
Vol 25 (12) ◽  
pp. 1441002 ◽  
Author(s):  
Yanbiao Gan ◽  
Aiguo Xu ◽  
Guangcai Zhang ◽  
Junqi Wang ◽  
Xijun Yu ◽  
...  
Keyword(s):  
Fourier Transform ◽  
Lattice Boltzmann ◽  
Present Model ◽  
Velocity Model ◽  
Interfacial Stress ◽  
Benchmark Tests ◽  
Temporal Derivative ◽  
Spatial Derivatives ◽  
Discrete Velocity Model ◽  
Liquid Vapor

We present a highly efficient lattice Boltzmann (LB) kinetic model for thermal liquid–vapor system. Three key components are as below: (i) a discrete velocity model (DVM) by Kataoka et al. [Phys. Rev. E69, 035701(R) (2004)]; (ii) a forcing term Ii aiming to describe the interfacial stress and recover the van der Waals (VDW) equation of state (EOS) by Gonnella et al. [Phys. Rev. E76, 036703 (2007)] and (iii) a Windowed Fast Fourier Transform (WFFT) scheme and its inverse by our group [Phys. Rev. E84, 046715 (2011)] for solving the spatial derivatives, together with a second-order Runge–Kutta (RK) finite difference scheme for solving the temporal derivative in the LB equation. The model is verified and validated by well-known benchmark tests. The results recovered from the present model are well consistent with previous ones [Phys. Rev. E84, 046715 (2011)] or theoretical analysis. The usage of less discrete velocities, high-order RK algorithm and WFFT scheme with 16th-order in precision makes the model more efficient by about 10 times and more accurate than the original one.

TIME-TO-CONTACT INFORMATION ESTIMATION FOR MONOCULAR MOBILE ROBOTS

2008 ◽  
Vol 05 (03) ◽  
pp. 223-233 ◽  
Author(s):  
RONG LIU ◽  
MAX Q. H. MENG
Keyword(s):  
Mobile Robots ◽  
Optical Flow ◽  
Active Contour Model ◽  
Visual Navigation ◽  
Moving Object ◽  
Time To Contact ◽  
Temporal Derivative ◽  
Novel Method ◽  
Derivatives Of ◽  
Flow Experiments

Time-to-contact (TTC) provides vital information for obstacle avoidance and for the visual navigation of a robot. In this paper, we present a novel method to estimate the TTC information of a moving object for monocular mobile robots. In specific, the contour of the moving object is extracted first using an active contour model; then the height of the motion contour and its temporal derivative are evaluated to generate the desired TTC estimates. Compared with conventional techniques employing the first-order derivatives of optical flow, the proposed estimator is less prone to errors of optical flow. Experiments using real-world images are conducted and the results demonstrate that the developed method can successfully achieve TTC with an average relative error (ARVE) of 0.039 with a single calibrated camera.

Local computation of optical flow using a silicon retina

2005 ◽  
Vol 36 (11) ◽  
pp. 12-23
Author(s):  
Kei Akiyama ◽  
Zhi-Wei Luo ◽  
Masaki Onishi ◽  
Tetsuya Yagi ◽  
Shigeyuki Hosoe
Keyword(s):  
Optical Flow ◽  
Local Computation ◽  
Silicon Retina

scholarly journals 252 A study on real-time detection of movement edge from on-vehicle camera image using silicon retina

2011 ◽  
Vol 2011.60 (0) ◽  
pp. _252-1_-_252-2_
Author(s):  
Tomonori KAMIYA ◽  
Yuusuke HIRAMATSU ◽  
Sigemichi OHSHIMA
Keyword(s):  
Real Time ◽  
Camera Image ◽  
Silicon Retina ◽  
Real Time Detection

scholarly journals Reciprocal Green's functions and the quick forecast of submarine landslide tsunamis

2020 ◽  
Vol 20 (3) ◽  
pp. 771-781 ◽  
Author(s):  
Guan-Yu Chen ◽  
Chin-Chih Liu ◽  
Janaka J. Wijetunge ◽  
Yi-Fung Wang
Keyword(s):  
Green's Functions ◽  
Green’S Functions ◽  
Submarine Landslide ◽  
Tsunami Source ◽  
Submarine Earthquakes ◽  
Temporal Derivative ◽  
Submarine Mass Failure ◽  
Tsunami Waveform ◽  
Tsunami Scenarios ◽  
Landslide Tsunamis

Abstract. Although tsunamis generated by submarine mass failure are not as common as those induced by submarine earthquakes, sometimes the generated tsunamis are higher than a seismic tsunami in the area close to the tsunami source, and the forecast is much more difficult. In the present study, reciprocal Green's functions (RGFs) are proposed as a useful tool in the forecast of submarine landslide tsunamis. The forcing in the continuity equation due to depth change in a landslide is represented by the temporal derivative of the water depth. After a convolution with reciprocal Green's function, the tsunami waveform can be obtained promptly. Thus, various tsunami scenarios can be considered once a submarine landslide happens, and a useful forecast can be formulated. When a submarine landslide occurs, the various possibilities for tsunami generation can be analyzed and a useful forecast can be devised.

scholarly journals The impact of the Chebyshev collocation method on solutions of the time-fractional Black–Scholes

2020 ◽  
Author(s):  
H. Mesgarani ◽  
A. Beiranvand ◽  
Y. Esmaeelzade Aghdam
Keyword(s):  
Collocation Method ◽  
Linear Interpolation ◽  
Stability And Convergence ◽  
Finite Domain ◽  
European Options ◽  
Chebyshev Collocation Method ◽  
Chebyshev Collocation ◽  
Black Scholes ◽  
Temporal Derivative ◽  
The Impact

AbstractThis paper presents a numerical solution of the temporal-fractional Black–Scholes equation governing European options (TFBSE-EO) in the finite domain so that the temporal derivative is the Caputo fractional derivative. For this goal, we firstly use linear interpolation with the $$(2-\alpha)$$ ( 2 - α ) -order in time. Then, the Chebyshev collocation method based on the second kind is used for approximating the spatial derivative terms. Applying the energy method, we prove unconditional stability and convergence order. The precision and efficiency of the presented scheme are illustrated in two examples.

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