Showing 1 - 20 results of 97 for search '(((( algorithm brain function ) OR ( algorithm step function ))) OR ( algorithm both function ))*', query time: 0.13s Refine Results
  1. 1

    Tracking analysis of the NLMS algorithm in the presence of both random and cyclic nonstationarities by Moinuddin, M.

    Published 2003
    “…The results show that, unlike in the stationary case, the steady-state excess MSE is not a monotonically increasing function of the step size. Moreover, the ability of the adaptive algorithm to track the variations in the environment is shown to degrade with increasing frequency offset.…”
    Get full text
    Get full text
    article
  2. 2
  3. 3

    New enumeration algorithm for regular boolean functions by Nasrallah, Walid F.

    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.…”
    Get full text
    Get full text
    Get full text
    Get full text
    conferenceObject
  4. 4
  5. 5

    A New Penalty Function Algorithm For Convex Quadratic Programming by Bendaya, M.

    Published 2020
    “…In this paper, we develop an exterior point algorithm for convex quadratic programming using a penalty function approach. …”
    Get full text
    article
  6. 6
  7. 7
  8. 8

    Kernel-Ridge-Regression-Based Randomized Network for Brain Age Classification and Estimation by Raveendra Pilli (21633287)

    Published 2024
    “…Effective and reliable assessment methods are required to accurately classify and estimate brain age. In this study, a brain age classification and estimation framework is proposed using structural magnetic resonance imaging (sMRI) scans, a 3-D convolutional neural network (3-D-CNN), and a kernel ridge regression-based random vector functional link (KRR-RVFL) network. …”
  9. 9

    Adaptive step-size sign least mean squares by Aldajani, M.A.

    Published 2004
    “…A powerful adaptation scheme is used to adapt the step-size of the sign function inside the recursion of the sign algorithm. …”
    Get full text
    Get full text
    article
  10. 10
  11. 11

    Consensus-Based Distributed Formation Control of Multi-Quadcopter Systems: Barrier Lyapunov Function Approach by Nargess Sadeghzadeh-Nokhodberiz (16904952)

    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. …”
  12. 12
  13. 13

    Optimum sensors allocation for drones multi-target tracking under complex environment using improved prairie dog optimization by Abu Zitar, Raed

    Published 2024
    “…This hybrid approach, the Improved Prairie Dog Optimization Algorithm (IPDOA) with the Genetic Algorithm (GA), utilizes the strengths of both algorithms to improve the overall optimization performance. …”
    Get full text
  14. 14
  15. 15

    Distributed optimal coverage control in multi-agent systems: Known and unknown environments by Mohammadhasan Faghihi (22303057)

    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. …”
  16. 16
  17. 17

    Iterative Least Squares Functional Networks Classifier by Faisal, Kanaan A

    Published 2007
    “…Both methodology and learning algorithm for this kind of computational intelligence classifier using the iterative least squares optimization criterion are derived. …”
    Get full text
    Get full text
    article
  18. 18

    Cross entropy error function in neural networks by Nasr, G.E.

    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. …”
    Get full text
    Get full text
    Get full text
    conferenceObject
  19. 19

    Autism Detection of MRI Brain Images Using Hybrid Deep CNN With DM-Resnet Classifier by JAIN, SWETA

    Published 2023
    “…Earlier diagnosis of ASD from brain image is necessary for reducing the effect of disorder. …”
    Get full text
    Get full text
  20. 20

    Tracking analysis of normalized adaptive algorithms by Moinuddin, M.

    Published 2003
    “…Close agreement between analytical analysis and simulation results is obtained for the case of the NLMS algorithm. The results show that, unlike the stationary case, the steady-state excess-mean-square error is not a monotonically increasing function of the step-size, while the ability of the adaptive algorithm to track the variations in the environment degrades by increasing the frequency offset.…”
    Get full text
    Get full text
    article