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Binary Space Topology Features in Applying to Transitional States Generation of Asynchronous Finite State Machine
The problem of a race free state assignment of an asynchronous automaton is considered. A method for the state assignment is suggested that provides the minimization of the number and theswitching activity of the memory elements along with the elimination of the critical races betweenthem.
High-current electron beam irradiation has been applied for surface coating of copper with aluminum in ablative mode at the TEMP-A accelerator with energy of 350 keV, pulse length of 5 μs, and fluence 10…200 J/cm2. The aluminum-rich surface layer with average thickness around 25 μm, microhardness of 6.7 GPa and elasticity modulus of 122 GPa was formed on the copper template. © 2015 National Science Center, Kharkov Institute of Physics and Technology. All rights reserved.
Computer-Aided synthesis of sequential functions of VLSI systems, such as microprocessor control units, must include design optimization procedures to yield area-effective circuits. We model sequential functions as deterministic synchronous Finite State Machines (FSM's), and we consider a regular and structured implementation by means of Programmable Logic Arrays (PLA's) and feedback registers. State assignment, i.e., binary encoding of the internal states of the finite state machine, affects substantially the silicon area taken by such an implementation. Several state assignment techniques have been proposed in the past. However, to the best of our knowledge, no Computer-Aided Design tool is in use today for an efficient encoding of control logic. We propose an algorithm for optimal state assignment. Optimal state assignment is based on an innovative strategy: logic minimization of the combinational component of the finite state machine is applied before state encoding. Logic minimization is performed on a symbolic (code independent) description of the finite state machine. The minimal symbolic representation defines the constraints of a new encoding problem, whose solutions are the state assignments that allow the implementation of the PLA with at most as many product-terms as the cardinality of the minimal symbolic representation. In this class, an optimal encoding is one of minimal length satisfying these constraints. A heuristic algorithm constructs a solution to the constrained encoding problem. The algorithm has been coded in a computer program, KISS, and tested on several examples of finite state machines. Experimental results have shown that the method is an effective tool for designing finite state machines.
In this study, an asynchronous wheelchair navigation system using a hybrid of EEG signal and EOG artifacts embedded in EEG signals is demonstrated. The EEG signals are recorded at three different locations on the scalp in the occipital and motor cortex regions. First, an EEG signal related to eyelid position is analyzed and used to determine whether the eyes are closed or open. If the eyes are closed, no wheelchair movement is allowed. If the eyes are open, EOG traces (artifacts) from two other EEG signals are examined to infer the gaze direction of the eyes. A sliding window is utilized to position important cues in the trace signals at the center of the window for effective classification. The variance of the EEG signal is used to determine the eyelid position by thresholding. Then, features extracted from the EOG traces are used as inputs to a pair of minimum distance classifiers whose outputs reveal the gaze shift performed by the eyes. The wheelchair navigation system is designed to move forward and backward in a total of six different directions. However, the number of distinct gaze direction that can be used as commands to move the wheelchair is only three. Therefore, we model the system as a finite state machine with three modes, each containing three states to overcome this deficiency. The system is equipped with proximity sensor to avoid collision with obstacles. A stop command is also available for safety measures. In a real-time experiment involving 20 participants, the system performed well as it registered a high accuracy of 97.88% with an average of computational time less than 1 s. The system was also tested by five participants in a navigation experiment where each participant successfully completed all tasks without collision while showing improvement in maneuvering ability over attempts.
Consider the Ants Nearby Treasure Search (ANTS) problem introduced by Feinerman, Korman, Lotker, and Sereni (PODC 2012), where n mobile agents, initially placed in a single cell of an infinite grid, collaboratively search for an adversarially hidden treasure. In this paper, the model of Feinerman et al. is adapted such that each agent is controlled by an asynchronous (randomized) finite state machine: they possess a constant-size memory and can locally communicate with each other through constant-size messages. Despite the restriction to constant-size memory, we show that their collaborative performance remains the same by presenting a distributed algorithm that matches a lower bound established by Feinerman et al. on the run-time of any ANTS algorithm.
This paper considers the applicability of a special type of graph, the boolean graph, for the state assignment problem of asynchronous sequential machines. It also utilizes the properties of a layer representation of a boolean graph for developing a method for deriving a connected row set assignment of an asynchronous sequential machine. This method provides, for quite a large number of flow tables, an assignment with minimal memory requirements or requiring one or two additional state variables.
THE SEARCH for simple abstract techniques to be applied to the design of switching systems is still, despite some recent advances, in its early stages. The problem in this area which has been attacked most energetically is that of the synthesis of efficient combinational that is, nonsequential, logic circuits.
The particle swarm optimization (PSO) algorithm, a relatively recent bio-inspired approach to solve combinatorial optimization problems mimicking the social behavior of birds flocking, is applied to problems of continuum structural topology design for the purpose of investigating optimal topologies and automatically creating innovative solutions. An overview of the PSO and binary PSO algorithms are first described. A discretized topology design representation and the method for mapping binary particle into this representation are then detailed. Subsequently, a modified binary PSO algorithm that adopts the concept of genotype–phenotype representation is illustrated. Several well-studied examples from structural topology optimization problems of minimum weight and minimum compliance are used to demonstrate its efficiency and versatility. The results indicate the effectiveness of the proposed algorithm and its ability to find families of structural topologies.
Asynchronous Sequential Machine Design and Analysis provides a lucid, in-depth treatment of asynchronous state machine design and analysis presented in two parts: Part I on the background fundamentals related to asynchronous sequential logic circuits generally, and Part II on self-timed systems, high-performance asynchronous programmable sequencers, and arbiters. Part I provides a detailed review of the background fundamentals for the design and analysis of asynchronous finite state machines (FSMs). Included are the basic models, use of fully documented state diagrams, and the design and characteristics of basic memory cells and Muller C-elements. Simple FSMs using C-elements illustrate the design process. The detection and elimination of timing defects in asynchronous FSMs are covered in detail. This is followed by the array algebraic approach to the design of single-transition-time machines and use of CAD software for that purpose, one-hot asynchronous FSMs, and pulse mode FSMs. Part I concludes with the analysis procedures for asynchronous state machines. Part II is concerned mainly with self-timed systems, programmable sequencers, and arbiters. It begins with a detailed treatment of externally asynchronous/internally clocked (or pausable) systems that are delay-insensitive and metastability-hardened. This is followed by defect-free cascadable asynchronous sequencers, and defect-free one-hot asynchronous programmable sequencers - their characteristics, design, and applications. Part II concludes with arbiter modules of various types, those with and without metastability protection, together with applications. Presented in the appendices are brief reviews covering mixed-logic gate symbology, Boolean algebra, and entered-variable K-map minimization. End-of-chapter problems and a glossary of terms, expressions, and abbreviations contribute to the reader's learning experience. Five productivity tools are made available specifically for use with this text and briefly discussed in the Preface.
Most of this chapter is based on an article by Scott Hauck.1 However, we have adapted this material to the style of the book, omitted certain topics, significantly changed other topics, and added new material.
This paper proposes an efficient critical race-free state assignment technique for Asynchronous Finite State Machines. Instead of using the Huffman model, it operates indirectly on the State Graph (SG) model, in which all signals are treated uniformedly and hazards can be characterized as a violation of the complete state coding (CSC) property. The proposed state assignment technique first detects CSC violations and then eliminates them using a modified greedy graph coloring heuristic.
This paper presents an automated method for the synthesis of multiple-input-change (MIC) asynchronous state machines. Asynchronous state machine design is subtle since, unlike synchronous synthesis, logic must be implemented without hazards, and state codes must be chosen carefully to avoid critical races. We formulate and solve an optimal hazard-free and critical race-free encoding problem for a class of MIC asynchronous state machines called burst-mode. Analogous to a paradigm successfully used for the optimal encoding of synchronous machines, the problem is formulated as an input encoding problem. Implementations are targeted to sum-of-product realizations. We believe this is the first general method for the optimal encoding of hazard-free MIC asynchronous state machines under a generalized fundamental mode of operation. Results indicate that improved solutions are produced, ranging up to 17% improvement
an efficient critical race-free state assignment technique for asynchronous finite state machines
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