IEEE

Towards Exascale Simulations of Nanoelectronic Devices in the GW Approximation

Abstract: Experimental development of gate-all-around silicon nanowire field-effect transistors (NWFETs), a viable replacement for FinFETs, can be complemented by technology computer-aided design.
IEEE

Fundamental Definition of Two-Stream Approximation for Radiative Transfer in Scattering Atmosphere

Abstract: The two-stream approximation (TSA) is a primary method for tackling radiative transfer in a scattering atmosphere, which has wide applications in radiation balance evaluation, atmospheric ...
IEEE

Universal Approximation Abilities of a Modular Differentiable Neural Network

Abstract: Approximation ability is one of the most important topics in the field of neural networks (NNs). Feedforward NNs, activated by rectified linear units and some of their specific smoothed ...
IEEE

Risk-Averse Trajectory Optimization via Sample Average Approximation

Abstract: Trajectory optimization under uncertainty underpins a wide range of applications in robotics. However, existing methods are limited in terms of reasoning about sources of epistemic and ...
IEEE

Proximity Index Value Based Systematized Approximation of Higher-Order Interconnected Power System Model

Abstract: The presented research proposal focuses on the approximation of higher-order (HO) multi-input multi-output (MIMO) interconnected power system model (IPSM) by employing systematic approach of ...
IEEE

A Numerical Approximation Approach for Deriving Computational Efficient Inverse Dynamics of 6-DOF Parallel Robots Based on Principle of Virtual Work

Abstract: The inverse dynamics of the six degree-of-freedom (6-DOF) parallel robot (PR) presents an inherent complexity due to the closed-loop kinematic chains. To derive computational efficient ...
IEEE

Gradient Approximation of Approximate Multipliers for High-Accuracy Deep Neural Network Retraining

Abstract: Approximate multipliers (AppMults) are widely employed in deep neural network (DNN) accelerators to reduce the area, delay, and power consumption. However, the inaccuracies of AppMults ...
IEEE

HV-Net: Hypervolume Approximation Based on DeepSets

Abstract: In this letter, we propose HV-Net, a new method for hypervolume approximation in evolutionary multiobjective optimization. The basic idea of HV-Net is to use DeepSets, a deep neural network ...
IEEE

Approximation-Aware Training for Efficient Neural Network Inference on MRAM Based CiM Architecture

Abstract: Convolutional neural networks (CNNs), despite their broad applications, are constrained by high computational and memory requirements. Existing compression techniques often neglect ...
IEEE

Exploring Approximation and Dataflow Co-Optimization for Scalable Transformer Inference Architecture on the Edge

Abstract: Transformer-based neural networks (NNs) prevail in today’s artificial intelligence applications, including autonomous driving, natural language processing and generative modeling, showing ...
IEEE

Local Low-Rank Approximation With Superpixel-Guided Locality Preserving Graph for Hyperspectral Image Classification

Abstract: Given the detrimental effect of spectral variations in a hyperspectral image (HSI), this article investigates to recover its discriminative representation to improve the classification ...
IEEE

Accelerated Successive Convex Approximation for Nonlinear Optimization-Based Control

Abstract: The successive convex approximation (SCA) methods stand out as the viable option for nonlinear optimization-based control, as it effectively addresses the challenges posed by nonlinear ...