  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 or a burst of codes is addressed, with reference to both
Single-Input Single-Output (SISO) and Multiple-Input Multiple-Output (MIMO)
radar systems. Two optimization machines, referred to as two-layer and
single-layer Binary Sequence Correlation Network (BiSCorN), able to learn
actions to design binary sequences with small ISL/Complementary ISL (CISL) for
SISO and MIMO systems are proposed. These two networks differ in terms of the
capability to synthesize Low-Correlation-Zone (LCZ) sequences and computational
cost. Numerical experiments show that proposed techniques can outperform
state-of-the-art algorithms for the design of binary sequences and
Complementary Sets of Sequences (CSS) in terms of ISL and, interestingly, of
Peak Sidelobe Level (PSL).
