Parallel, asynchronous, fuzzy logic systems realized in CMOS technology
- PDF / 1,735,021 Bytes
- 17 Pages / 439.642 x 666.49 pts Page_size
- 76 Downloads / 241 Views
Parallel, asynchronous, fuzzy logic systems realized in CMOS technology Tomasz Tala´ska1 Received: 30 September 2018 / Accepted: 18 December 2018 / © The Author(s) 2019
Abstract Fuzzy systems play an important role in many industrial applications. Depending on the application, they can be implemented using different techniques and technologies. Software implementations are the most popular, which results from the ease of such implementations. This approach facilitates modifications and testing. On the other hand, such realizations are usually not convenient when high data rate, low cost per unit, and large miniaturization are required. For this reason, we propose efficient, fully digital, parallel, and asynchronous (clock-less) fuzzy logic (FL) systems suitable for the implementation as ultra low-power-specific integrated circuits (ASICs). On the basis of our former work, in which single FL operators were proposed, here we demonstrate how to build larger structures, composed of many operators of this type. As an example, we consider Lukasiewicz neural networks (LNN) that are fully composed of selected FL operators. In this work, we propose FL OR, and AND Lukasiewicz neurons, which are based on bounded sum and bounded product FL operators. In the comparison with former analog implementations of such LNNs, digital realization, presented in this work, offers important advantages. The neurons have been designed in the CMOS 130nm technology and thoroughly verified by means of the corner analysis in the HSpice environment. The only observed influence of particular combinations on the process, voltage, and temperature parameters was on delays and power dissipation, while from the logical point of view, the system always worked properly. This shows that even larger FL systems may be implemented in this way. Keywords Fuzzy logic systems · FL operators · FL neural networks · Asynchronous circuits · Parallel circuits · CMOS implementation
Communicated by: Pavel Solin Tomasz Tala´ska
[email protected] 1
Faculty of Telecommunication, Computer Science and Electrical Engineering, UTP University of Science and Technology, ul. Kaliskiego 7, 85-796, Bydgoszcz, Poland
T. Tala´ska
Mathematics Subject Classification (2010) 68T27
1 Introduction The popularity of fuzzy logic systems (FLS) results from the fact that the real world is analog (multivalued). Additionally, in solving real problems, we use a fuzzy approach in a natural way. Bivalent logic is often insufficient, as its hard selection between the TRUE and the FALSE values may lead to curious situations. For example, a group of children may be divided into low and tall on the basis of their height. If we define the limits between two sets, for example, as 110 cm, then in bivalent logic children with the heights of 109.99 cm and 110.01 cm will belong to two different sets. Fuzzy sets that allow the two children to belong to both sets with different percentage are more natural in such situations. Thanks to various interesting properties of the FLSs, they have found
Data Loading...
