A Learning-Inspired Strategy to Design Binary Sequences With Good Correlation Properties: SISO and MIMO Radar Systems
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Aerospace and Electronic Systems"
DOI: 10.1109/taes.2023.3280468
Abstract: In this paper, the design of binary sequences exhibiting low values of aperiodic/periodic correlation functions, in terms of Integrated Sidelobe Level (ISL), is pursued via a learning-inspired method. Specifcally, the synthesis of either a single… read more here.
Keywords: learning inspired; binary sequences; correlation; design binary ... See more keywords
Manifold Learning-Inspired Mating Restriction for Evolutionary Multiobjective Optimization With Complicated Pareto Sets
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Transactions on Cybernetics"
DOI: 10.1109/tcyb.2019.2952881
Abstract: Under certain smoothness assumptions, the Pareto set of a continuous multiobjective optimization problem is a piecewise continuous manifold in the decision space, which can be derived from the Karush–Kuhn–Tucker condition. Despite that a number of… read more here.
Keywords: learning inspired; optimization; pareto sets; manifold learning ... See more keywords