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Predicting Compression Modes and Split Decisions for HEVC Video Coding Using Machine Learning Techniques
Published 2017Get full text
doctoralThesis -
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Large language models for code completion: A systematic literature review
Published 2024“…Different techniques can achieve code completion, and recent research has focused on Deep Learning methods, particularly Large Language Models (LLMs) utilizing Transformer algorithms. …”
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Scalable parallel algorithms for difficult combinatorial problems
Published 2004“…To accomplish this, an efficient sequential algorithm and two forms of parallel algorithms are implemented. …”
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conferenceObject -
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Synthesis of MVL Functions - Part I: The Genetic Algorithm Approach
Published 2006“…Multiple-Valued Logic (MVL) has been used in the design of a number of logic systems, including memory, multi-level data communication coding, and a number of special purpose digital processors. …”
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Optimized FPGA Implementation of PWAM-Based Control of Three—Phase Nine—Level Quasi Impedance Source Inverter
Published 2019“…Since, PWAM control algorithm is more complex than PSCPWM, FPGA based implementation for PWAM control is discussed. …”
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Sample intelligence-based progressive hedging algorithms for the stochastic capacitated reliable facility location problem
Published 2024“…In this paper, we developed two novel algorithms integrating SAA and PHA for solving the CRFLP under uncertainty. …”
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Sensitivity analysis and genetic algorithm-based shear capacity model for basalt FRC one-way slabs reinforced with BFRP bars
Published 2023“…Finally, a design equation that can predict the shear capacity of one-way BFRC-BFRP slabs was proposed based on genetic algorithm. The proposed model showed the best prediction accuracy compared to the available design codes and guidelines with a mean of predicted to experimental shear capacities (V<sub>pred</sub>/V<sub>exp</sub>) ratio of 0.97 and a coefficient of variation of 17.91%.…”
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Multi Self-Organizing Map (SOM) Pipeline Architecture for Multi-View Clustering
Published 2024“…A self-organizing map is one of the well-known unsupervised neural network algorithms used for preserving typologies during mapping from the input space (high-dimensional) to the display (low-dimensional).An algorithm called Local Adaptive Receptive Field Dimension Selective Self-Organizing Map 2 is a modified form of a self-organizing Map to cater different data types in the dataset. …”
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Efficient Seismic Volume Compression using the Lifting Scheme
Published 2000“…Finally a runlength plus a Huffman encoding are applied for binary coding of the quantized coefficients.…”
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Developing a Cooperative Behavior for Multi Agents System Application to Robot Soccer
Published 2007Get full text
doctoralThesis -
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Multigrid solvers in reconfigurable hardware. (c2006)
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masterThesis -
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Downlink channel estimation for IMT-DS
Published 2001“…To obtain channel estimates during pilot symbols, we propose a chip level adaptive channel estimation which performs better than the conventional method. …”
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Measuring ripple effect for object-oriented programs. (c2004)
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masterThesis -
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Spectral energy balancing system with massive MIMO based hybrid beam forming for wireless 6G communication using dual deep learning model
Published 2024“…The performance level improvements are practically summarized in both the transmission and reception entities with the help of the proposed hybrid network architecture and the associated Dual Deep Network algorithm. …”
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Ultra-small cell networks with collaborative RF and lightwave power transfer
Published 2019“…This scheme leads to the formulation of two optimization problems that correspond to the resource allocation at the optical transmitters and the RF AP. …”
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Advanced Quantum Control with Ensemble Reinforcement Learning: A Case Study on the XY Spin Chain
Published 2025“…<p dir="ltr">This research presents an ensemble Reinforcement Learning (RL) approach that combines Deep Q-Network (DQN) and Proximal Policy Optimization (PPO) algorithms to tackle quantum control problems. This research aims to use the complementary strengths of DQN and PPO algorithms to develop robust and adaptive control policies for noisy and uncertain quantum systems. …”