A connection-constraint algorithm for a sparse adaptive photonic filter

A sparse reconfigurable adaptive filter (SRAF) for a photonic switch consists of a large number of input and output delays, sparse reconfigurable connections, and adaptive weights. Recently, it was shown that a modified system-based (MSB) algorithm for the SRAF is more efficient than conventional algorithms such as previously introduced cross-correlation-based (CCB) and system-based (SB) approaches. In this paper, we propose a connection constraint for the MSB algorithm that chooses the most effective elements among the entire connection matrix. The proposed method allows any input to be connected to any output with an arbitrary weight, and is more efficient than the approaches mentioned above due to its reduced computational complexity. We provide a computer simulation example to demonstrate the performance of the connection-constraint algorithm for a system identification application.