D
Durbadal Mandal
Researcher at National Institute of Technology, Durgapur
Publications - 454
Citations - 4262
Durbadal Mandal is an academic researcher from National Institute of Technology, Durgapur. The author has contributed to research in topics: Particle swarm optimization & Antenna array. The author has an hindex of 27, co-authored 409 publications receiving 3297 citations. Previous affiliations of Durbadal Mandal include Hindustan College of Science and Technology.
Papers
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Book ChapterDOI
Infinite Impulse Response Approximations to the Non-integer Order Integrator Using Cuckoo Search Algorithm
TL;DR: Comparisons on the basis of design quality robustness, error convergence, and optimization time of the CSA-based NOIs carried out with the Particle Swarm Optimization (PSO) based designs demonstrate the efficient performance of CSA in exploring the multimodal, non-linear, and non-uniform error surface for this optimization problem.
Journal ArticleDOI
Discrete Non-Integer Order Differentiator Models Using Moth-Flame Optimization Algorithm
TL;DR: The effectiveness of MFO in outperforming PSO-w in solving this non-linear and multimodal optimization problem is demonstrated and the proposed DNODs exhibit better performance in comparison with the designs based on techniques such as Nelder-Mead Simplex algorithm and Cuckoo Search Algorithm published in recent literature.
Proceedings ArticleDOI
Optimal Synthesis of Linear Antenna Array with wide Null Symmetry Using Novel Particle Swarm Optimization Technique
TL;DR: Imposing nulls in the radiation pattern of a symmetric linear array antenna with constant phase and excitation current but different in spacing between the elements is dealt in this paper using NPSO technique.
Book ChapterDOI
Current-Phase Synthesis of Linear Antenna Arrays Using Particle Swarm Optimization Variants
TL;DR: Variants of particle swarm optimization, like Grey PSO and Novel PSO, are adopted for dealing with the problem of low sidelobe phased array synthesis, and effect of position regulation and inertia control strategies on the convergence of PSO variants is studied.
Book ChapterDOI
Design and Simulation of FIR High Pass Filter Using Gravitational Search Algorithm
TL;DR: Extensive simulation results justify the superiority and optimization efficacy of the GSA over the afore-mentioned optimization techniques for the solution of the multimodal, non-differentiable, highly non-linear, and constrained filter design problems.