The objective of this paper is to investigate and find a solution by designing the intelligent controllers for controlling water level system, such as fuzzy logic and neural network. The controllers also can be specifically run under the circumstance of system disturbances. To achieve these objectives, a prototype of water level control system has been built and implementations of both fuzzy lo...

Road accident prediction plays an important role in accessing and improving the road safety. Besides the conventional generalized linear regression, the prediction approaches based on fuzzy logic and neural networks have increasingly been proven to have a significant accident-predicting capability in recent years. However, fuzzy logic and neural network have their respective limitations. For ex...

This paper presents a discrete device for neural network realized on field-programmable gate arrays (FPGA). A basic element of the implemented neural network is new type of neuron, called Boolean neuron that may be mapped directly to configurable logic blocks (CLB) or to look up table (LUT) of FPGAs. The structure and logic of the Boolean neuron allows a direct representation of the Boolean neu...

A static model for the parallel execution of logic programs on MIMD distributed memory systems is presented where a refutation is implemented through a process network returned by the compilation of the logic program. The model supports Restricted-AND, OR and stream parallelism and it is integrated with a set of static analyses to optimise the process network. Altogether, the processes interact...

This work describes a methodology that combines logic-based systems and connectionist systems. Our approach uses finite truth-valued Lukasiewicz logic, wherein every connective can be defined by a neuron in an artificial network [1]. This allowed the injection of first-order formulas into a network architecture, and also simplified symbolic rule extraction. For that we trained a neural networks...

Neural Logic Network or Neulonet is a hybrid of neural network expert systems. Its strength lies in its ability to learn and to represent human logic in decision making using component net rules. The technique originally employed in neulonet learning is backpropagation. However, the resulting weight adjustments will lead to a loss in the logic of the net rules. A new technique is now developed ...

The growing variability and complexity of advanced CMOS technologies makes the physical design of clocked logic in large Systems-on-Chip more and more challenging. Asynchronous logic has been studied for many years and become an attractive solution for a broad range of applications, from massively parallel multi-media systems to systems with ultra-low power & low-noise constraints, like cryptog...

Undoubtedly, public spaces can be considered as an essential factor, which could contribute to urban arrangement, create and maintain a strong local center and enhance the quality of superior environment and the sense of citizenship. Moreover, integrity has always been the most basic structural qualities and one of the key principles of cities. Integrated urban spaces exhibit the integrated str...

In this paper, we present area and performance-driven clustering techniques for coarse-grained, antifuse-based FPGAs. A macro logic cell in this class of FPGAs has multiple inputs and multiple outputs. Starting with this macro cell, a library of small logic cells can be generated and a target network was mapped with the library. For the minimum-area clustering, our algorithm minimizes the numbe...

This paper describes a new approach for the minimization of multilevel logic circuits. We define a multilevel representation of a block of combinational logic called a Boolean network. We propose a procedure, ESPRESSO-MLD, to transform a given Boolean network into a prime, irredundant, and “R-minimal” form. This procedure rests on the extension of the notions of primality and irredundancy, prev...