Multiset Signal Processing and Electronics

• URL: http://arxiv.org/abs/2111.08514v1
• Date: Sat, 13 Nov 2021 11:50:00 GMT
• Title: Multiset Signal Processing and Electronics
• Authors: Luciano da F. Costa
• Abstract summary: Multisets are intuitive extensions of the traditional concept of sets that allow repetition of elements. Recent generalizations of multisets to real-valued functions have paved the way to a number of interesting implications and applications. It is proposed that effective multiset operations capable of high performance self and cross-correlation can be obtained with relative simplicity in either discrete or integrated circuits.
• Score: 1.0152838128195467
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: Multisets are an intuitive extension of the traditional concept of sets that allow repetition of elements, with the number of times each element appears being understood as the respective multiplicity. Recent generalizations of multisets to real-valued functions, accounting for possibly negative values, have paved the way to a number of interesting implications and applications, including respective implementations as electronic systems. The basic multiset operations include the set complementation (sign change), intersection (minimum between two values), union (maximum between two values), difference and sum (identical to the algebraic counterparts). When applied to functions or signals, the sign and conjoint sign functions are also required. Given that signals are functions, it becomes possible to effectively translate the multiset and multifunction operations to analog electronics, which is the objective of the present work. It is proposed that effective multiset operations capable of high performance self and cross-correlation can be obtained with relative simplicity in either discrete or integrated circuits. The problem of switching noise is also briefly discussed. The present results have great potential for applications and related developments in analog and digital electronics, as well as for pattern recognition, signal processing, and deep learning.

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