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algorithm allows » algorithm aoa (Expand Search)
algorithm both » algorithm goa (Expand Search), algorithm aoa (Expand Search), algorithm its (Expand Search)
cell function » cost function (Expand Search)
both function » cost function (Expand Search)
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1
New fault models and efficient BIST algorithms for dual-portmemories
Published 1997“…These modifications allow multiple access of memory cells for increased test speed with minimal overhead on both silicon area and device performance. …”
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2
Design and Implementation of an Advanced Control and Guidance Algorithm of a Single Rotor Helicopter
Published 2013Get full text
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New enumeration algorithm for regular boolean functions
Published 2018“…After proving this equivalence, this paper introduces a novel data structure that may, with further tweaking, enable faster enumeration algorithms for both regular Boolean functions and all-capacities knapsack problem instances.…”
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conferenceObject -
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A hybridization of evolution strategies with iterated greedy algorithm for no-wait flow shop scheduling problems
Published 2024“…<p dir="ltr">This study investigates the no-wait flow shop scheduling problem and proposes a hybrid (HES-IG) algorithm that utilizes makespan as the objective function. …”
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Optimization of Commercially Off the Shelf (COTS) Electric Propulsion System for Low Speed Fuel Cell UAV
Published 2013Get full text
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7
A parallel tabu search algorithm for VLSI standard-cell placement
Published 2000“…VLSI standard-cell placement is an NP-hard problem to which various heuristics have been applied. …”
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GATS: A Novel Hybrid Algorithm for Multiobjective Cell Placement in VLSI Circuit Design
Published 2020“…This paper addresses the optimization of cell placement step in VLSI circuit design [1]. A novel hybrid algorithm is proposed for performance and low power driven VLSI standard cell placement. …”
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Automatic image quality evaluation in digital radiography using a modified version of the IAEA radiography phantom allowing multiple detection tasks
Published 2025“…The modulation transfer function (MTF) and the signal‐to‐noise‐ratio (SNR) dependence on exposure conditions and post‐processing algorithms do not always follow the same trends for raw and clinical images and/or different manufacturers, while the signal‐difference‐to‐noise‐ratio (SDNR) and the detectability index (d′), despite their differences, seem more appropriate to characterize IQ. …”
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Consensus-Based Distributed Formation Control of Multi-Quadcopter Systems: Barrier Lyapunov Function Approach
Published 2023“…The method is firstly developed in a centralized scheme and then extended to a distributed framework using appropriate asymptotically convergent consensus algorithms. Therefore, the asymptotic convergence of the designed distributed algorithm to the centralized one is guaranteed. …”
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Accommodating High Penetrations of Renewable Distributed Generation Mix in Smart Grids
Published 2017Get full text
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13
Distributed optimal coverage control in multi-agent systems: Known and unknown environments
Published 2024“…The proposed technique offers an optimal solution with a lower cost with respect to conventional Voronoi-based techniques by effectively handling the issue of agents remaining stationary in regions void of information using a ranking function. The proposed approach leverages a novel cost function for optimizing the agents’ coverage and the cost function eventually aligns with the conventional Voronoi-based cost function. …”
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High-Accurate Parameter Identification of PEMFC Using Advanced Multi-Trial Vector-Based Sine Cosine Meta-Heuristic Algorithm
Published 2025“…The trigonometric function-based sine cosine algorithm (SCA) may solve such problems, but it traps in local optima, making it inappropriate for larger optimization tasks. …”
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Iterative Least Squares Functional Networks Classifier
Published 2007“…Both methodology and learning algorithm for this kind of computational intelligence classifier using the iterative least squares optimization criterion are derived. …”
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Cross entropy error function in neural networks
Published 2002“…The ANN is implemented using the cross entropy error function in the training stage. The cross entropy function is proven to accelerate the backpropagation algorithm and to provide good overall network performance with relatively short stagnation periods. …”
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Evolution Of Activation Functions for Neural Architecture Search
Published 2020“…The introduction of the ReLU function in neural network architectures yielded substantial improvements over sigmoidal activation functions and allowed for the training of deep networks. …”
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masterThesis -
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Stochastic evolution algorithm for technology mapping
Published 1998“…SELF-Map is based on the Stochastic Evolution (SE) algorithm. The state space model of the problem is defined and suitable cost function which allows optimization for area, delay, or area-delay combinations is proposed. …”
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Development of an Optimization Scheme for A Fixed-Wing UAV Long Endurance with PEMFC and Battery
Published 2018Get full text
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Bridge Structural Health Monitoring Using Mobile Sensor Networks
Published 2022Get full text
doctoralThesis