The AI conversation is still too narrowly framed. Most debates assume intelligence is fundamentally computational, that ...
Abstract: We propose a largely output-sensitive visualization method for 3D line integral convolution (LIC) whose rendering speed is mainly independent of the data set size and mostly governed by the ...
Simulation of GEMM and convolution (as im2col) operations Analytical compute cycles validated by RTL simulation Separate double-buffered memory modeling for Input, Filter and Output matrices ...
Our research proves a conjecture from string theory asserting the vanishing of a specific convolution sum arising in the 4-graviton scattering amplitude in 10-dimensional type IIB string theory. The ...
This study centers on incorporating memory effects (the impact of past events on current states) into mathematical models for population dynamics. It introduces a framework based on the gamma ...
Compute-in-memory (CIM) is gaining attention due to its efficiency in limiting the movement of massive volumes of data, but it’s not perfect. CIM modules can help reduce the cost of computation for AI ...
Elastic full waveform inversion (EFWI) is a powerful technique. However, its strong non-linearity makes it susceptible to converging towards local extremes during the iterative process due to various ...
The effective analysis methods for steady-state visual evoked potential (SSVEP) signals are critical in supporting an early diagnosis of glaucoma. Most efforts focused on adopting existing techniques ...
Abstract: Accurate analysis of susceptibility of circuits from damage due to electrostatic discharges (ESDs), electromagnetic pulses, and lightning effects is required to ensure reliable operation of ...
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