23,312 research outputs found
Recommended from our members
Pseudorandom number generation with self programmable cellular automata
In this paper, we propose a new class of cellular automata ā self programming cellular automata (SPCA) with specific application to pseudorandom number generation. By changing a cell's state transition rules in relation to factors such as its neighboring cell's states, behavioral complexity can be increased and utilized. Interplay between the state transition neighborhood and rule selection neighborhood leads to a new composite neighborhood and state transition rule that is the linear combination of two different mappings with different temporal dependencies. It is proved that when the transitional matrices for both the state transition and rule selection neighborhood are non-singular, SPCA will not exhibit non-group behavior. Good performance can be obtained using simple neighborhoods with certain CA length, transition rules etc. Certain configurations of SPCA pass all DIEHARD and ENT tests with an implementation cost lower than current reported work. Output sampling methods are also suggested to improve output efficiency by sampling the outputs of the new rule selection neighborhoods
Talking quiescence: a rigorous theory that supports parallel composition, action hiding and determinisation
The notion of quiescence - the absence of outputs - is vital in both
behavioural modelling and testing theory. Although the need for quiescence was
already recognised in the 90s, it has only been treated as a second-class
citizen thus far. This paper moves quiescence into the foreground and
introduces the notion of quiescent transition systems (QTSs): an extension of
regular input-output transition systems (IOTSs) in which quiescence is
represented explicitly, via quiescent transitions. Four carefully crafted rules
on the use of quiescent transitions ensure that our QTSs naturally capture
quiescent behaviour.
We present the building blocks for a comprehensive theory on QTSs supporting
parallel composition, action hiding and determinisation. In particular, we
prove that these operations preserve all the aforementioned rules.
Additionally, we provide a way to transform existing IOTSs into QTSs, allowing
even IOTSs as input that already contain some quiescent transitions. As an
important application, we show how our QTS framework simplifies the fundamental
model-based testing theory formalised around ioco.Comment: In Proceedings MBT 2012, arXiv:1202.582
Formal Modeling of Connectionism using Concurrency Theory, an Approach Based on Automata and Model Checking
This paper illustrates a framework for applying formal methods techniques, which are symbolic in nature, to specifying and verifying neural networks, which are sub-symbolic in nature. The paper describes a communicating automata [Bowman & Gomez, 2006] model of neural networks. We also implement the model using timed automata [Alur & Dill, 1994] and then undertake a verification of these models using the model checker Uppaal [Pettersson, 2000] in order to evaluate the performance of learning algorithms. This paper also presents discussion of a number of broad issues concerning cognitive neuroscience and the debate as to whether symbolic processing or connectionism is a suitable representation of cognitive systems. Additionally, the issue of integrating symbolic techniques, such as formal methods, with complex neural networks is discussed. We then argue that symbolic verifications may give theoretically well-founded ways to evaluate and justify neural learning systems in the field of both theoretical research and real world applications
Testing Identifiable Kernel P Systems Using an X-machine Approach
This paper presents a testing approach for kernel P systems (kP systems),
based on the X-machine testing framework and the concept of cover automaton. The
testing methodology ensures that the implementation conforms the speci cations, under
certain conditions, such as the identi ably concept in the context of kernel P systems
- ā¦