# Answering An Open Problem on $T$-Norms for Type-2 Fuzzy Sets

## TL;DR

This paper proves that certain convolution-based operations on functions over [0,1] are t-norms or t-conorms, resolving an open problem and characterizing their properties in the context of Type-2 fuzzy sets.

## Contribution

It establishes that specific convolution operations are t-norms or t-conorms, answering a previously open question and providing new insights into their characteristics.

## Key findings

- Confirmed convolution operations are t-norms or t-conorms.
- Provided characterizations of t-norm and t-conorm via convolution operations.
- Resolved an open problem from prior research.

## Abstract

This paper proves that a binary operation ${\star}$ on ${[0, 1]}$, ensuring that the binary operation ${\curlywedge}$ is a ${t}$-norm or ${\curlyvee}$ is a ${t}$-conorm, is a ${t}$-norm, where ${\curlywedge}$ and ${\curlyvee}$ are special convolution operations defined by $${(f\curlywedge g)(x)=\sup\left\{f(y)\star g(z): y\vartriangle z=x\right\},} $$ $${(f\curlyvee g)(x)=\sup\left\{f(y)\star g(z): y\ \triangledown\ z=x\right\},} $$ for any ${f, g\in Map([0, 1], [0, 1])}$, where ${\vartriangle}$ and ${\triangledown}$ are a continuous ${t}$-norm and a continuous ${t}$-conorm on ${[0, 1]}$, answering negatively an open problem posed in \cite{HCT2015}. Besides, some characteristics of ${t}$-norm and ${t}$-conorm are obtained in terms of the binary operations ${\curlywedge}$ and ${\curlyvee}$.