1,411 research outputs found
Modelling Nonlinear Sequence Generators in terms of Linear Cellular Automata
In this work, a wide family of LFSR-based sequence generators, the so-called
Clock-Controlled Shrinking Generators (CCSGs), has been analyzed and identified
with a subset of linear Cellular Automata (CA). In fact, a pair of linear
models describing the behavior of the CCSGs can be derived. The algorithm that
converts a given CCSG into a CA-based linear model is very simple and can be
applied to CCSGs in a range of practical interest. The linearity of these
cellular models can be advantageously used in two different ways: (a) for the
analysis and/or cryptanalysis of the CCSGs and (b) for the reconstruction of
the output sequence obtained from this kind of generators.Comment: 15 pages, 0 figure
Linear solutions for cryptographic nonlinear sequence generators
This letter shows that linear Cellular Automata based on rules 90/150
generate all the solutions of linear difference equations with binary constant
coefficients. Some of these solutions are pseudo-random noise sequences with
application in cryptography: the sequences generated by the class of shrinking
generators. Consequently, this contribution show that shrinking generators do
not provide enough guarantees to be used for encryption purposes. Furthermore,
the linearization is achieved through a simple algorithm about which a full
description is provided
1D Cellular Automata for Pulse Width Modulated Compressive Sampling CMOS Image Sensors
Compressive sensing (CS) is an alternative to the Shannon limit when the signal to be acquired is known to be sparse or compressible in some domain. Since compressed samples are non-hierarchical packages of information, this acquisition technique can be employed to overcome channel losses and restricted data rates. The quality of the compressed samples that a sensor can deliver is affected by the measurement matrix used to collect them. Measurement matrices usually employed in CS image sensors are recursive random-like binary matrices obtained using pseudo-random number generators (PRNG). In this paper we analyse the performance of these PRNGs in order to understand how their non-idealities affect the quality of the compressed samples. We present the architecture of a CMOS image sensor that uses class-III elementary cellular automata (ECA) and pixel pulse width modulation (PWM) to generate onchip a measurement matrix and high the quality compressed samples.Ministerio de EconomĂa y Competitividad TEC2015-66878-C3-1-RJunta de AndalucĂa TIC 2338-2013Office of Naval Research N000141410355CONACYT (Mexico) MZO-2017-29106
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