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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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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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New Fast Arctangent Approximation Algorithm for Generic Real-Time Embedded Applications
Published 2019“…The new algorithm exploits the pseudo-linear region around the tangent function zero point to estimate a reduced input arctangent through a modified rational approximation before referring this estimate to its original value using miniature LUTs. …”
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Shuffled Linear Regression with Erroneous Observations
Published 2019“…We propose an optimal recursive algorithm that updates the estimate from the underdetermined function that is based on that permutation-invariant constraint. …”
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Using machine learning algorithm for detection of cyber-attacks in cyber physical systems
Published 2022“…In the event of a violation in internet security, an attacker was able to interfere with the system's functions, which might result in catastrophic consequences. …”
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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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Design and Implementation of an Advanced Control and Guidance Algorithm of a Single Rotor Helicopter
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ANT-colony optimization-direct torque control for a doubly fed induction motor : An experimental validation
Published 2022“…For that reason, this work is focused on the theoretical studies and experimental validation on dSPACE Board DS1104 of the new proposed approach based on PID speed regulation, optimized by the Ant Colony Optimization algorithm (ACO) for DTC, applied to both sides of the Doubly Fed Induction Motor (DFIM), to overcome the previous drawbacks cited at the beginning. …”
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On Indefinite Quadratic Optimization over the Intersection of Balls and Linear Constraints
Published 2022“…<p>In this paper, we study the minimization of an indefinite quadratic function over the intersection of balls and linear inequality constraints (QOBL). …”
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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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From Collatz Conjecture to chaos and hash function
Published 2023“…<p>The non-linear property of Chaos is a promising approach to information security, and many accomplishments have been made by combining Chaos with several sub-security domains, including chaos-based stream ciphers, block ciphers, image encryption, and hash functions. …”
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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“…However, to the best of our knowledge, the design of new activation functions has mostly been done by hand. In this work, we propose the use of a self-adaptive evolutionary algorithm that searches for new activation functions using a genetic programming approach, and we compare the performance of the obtained activation functions to ReLU. …”
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masterThesis