The synthesis of periodic sequential machines
Conversion of sequential machine into periodic one, with savings in logical elements
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Conversion of sequential machine into periodic one, with savings in logical elements
Algorithm determining sequential machine error partition representing inessential errors
Generalized decomposition theory of finite sequential machines
Finite-state sequential machine model - proof of equivalence and procedures for transforming one model to other preserving machine minimality
Inessential errors characterization in sequential machines by algorithm for computing error partition
Memory cell fault tolerant sequential machine synthesis, considering masking feasibility and lower bounds on minimum redundancy
Permanent memory faults effects on sequential machines finite-state behavior, considering masking role in synthesis of fault-tolerant sequential networks
A method is described for determining the realizability of a sequential machine with trigger or set-reset flip-flop memory elements when the feedback of the machine is given by a Boolean function. Feedbacks in several types of sequential machines with different memory elements are compared, showing the memory specifications allowing the realization of such machines.
Language and algorithm for abstract synthesis of sequential machine - systems design
This report presents a description of a computer program mechanized to perform the Paull and Unger process of simplifying incompletely specified sequential machines. An understanding of the process, as given in Ref. 3, is a prerequisite to the use of the techniques presented in this report. This process has specific application in the design of asynchronous digital machines and was used in the design of operational support equipment for the Mariner 1966 central computer and sequencer. A typical sequential machine design problem is presented to show where the Paull and Unger process has application. A description of the Paull and Unger process together with a description of the computer algorithms used to develop the program mechanization are presented. Several examples are used to clarify the Paull and Unger process and the computer algorithms. Program flow diagrams, program listings, and a program user operating procedures are included as appendixes.
Decoder analysis for convolutional codes by stochastic sequential machine model
Convolutional code decoder modeled as autonomous stochastic sequential machine, considering finite Markov chain theory for error probability
A new fault-tolerant state assignment method is suggested for synchronous sequential machines. It is assumed that the inputs are fault free and that for no input it is possible to reach all or most of the states, whose number may be fairly large. Error correcting codes for the state assignment are generated by permutations of a chosen linear code. A state assignment algorithm is developed and its computational complexity is estimated. Examples are given.
Algorithm for assigning binary codes to inputs, internal states and outputs for sequential machines by threshold logic
Decomposition theory principles are used in developing a method of obtaining low-cost state variable assignments for sequential machines
Feedback and inessential errors in sequential machines, realization of sequential machines, and logic hazards in threshold gate networks
Representation of a memory fault of a sequential machine M by a function mu on the states of M and the result of the fault by an appropriately determined machine M(mu). Given some sequential behavior B, its inherent tolerance to memory faults can then be measured in terms of the minimum memory redundancy required to realize B with a state-assigned machine having fault tolerance type tau and fault tolerance level t. A behavior having maximum inherent tolerance is exhibited, and it is shown that behaviors of the same size can have different inherent tolerance.