scholarly journals LAYERED CELLULAR AUTOMATA FOR PSEUDORANDOM NUMBER GENERATION

2007 ◽  
Vol 18 (02) ◽  
pp. 217-234
Author(s):  
SYN KIAT TAN ◽  
SHENG-UEI GUAN
Keyword(s):  
Cellular Automata ◽  
Linear Function ◽  
Phase Difference ◽  
Linear Complexity ◽  
Maximum Length ◽  
Operating Speed ◽  
Time Varying ◽  
Nonlinear Functions ◽  
Initial States ◽  
Pseudorandom Number Generation

The proposed Layered Cellular Automata (L-LCA), which comprises of a main CA with L additional layers of memory registers, has simple local interconnections and high operating speed. The time-varying L-LCA transformation at each clock can be reduced to a single transformation in the set {Af | f = 1, 2, …, 2n -1} formed by the transformation matrix A of a maximum length Cellular Automata (CA), and the entire transformation sequence for a single period can be obtained. The analysis for the period characteristics of state sequences is simplified by analyzing representative transformation sequences determined by the phase difference between the initial states for each layer. The L-LCA model can be extended by adding more layers of memory or through the use of a larger main CA based on widely available maximum length CA. Several L-LCA (L = 1, 2, 3, 4) with 10- to 48-bit main CA are subjected to the DIEHARD test suite and better results are obtained over other CA designs reported in the literature. The experiments are repeated using the well-known nonlinear functions f30 and f45 in place of the linear function f204 used in the L-LCA. Linear complexity is significantly increased when f30 or f45 is used.

scholarly journals A TRANSFORMATION SEQUENCING APPROACH TO PSEUDORANDOM NUMBER GENERATION

2007 ◽  
Vol 18 (08) ◽  
pp. 1293-1302
Author(s):  
SYN KIAT TAN ◽  
SHENG-UEI GUAN
Keyword(s):  
Cellular Automata ◽  
Uniform Distribution ◽  
Design Patterns ◽  
Maximum Length ◽  
Pseudorandom Number ◽  
New Approach ◽  
Balanced Distribution ◽  
Pseudorandom Number Generation ◽  
Important Design ◽  
Randomness Tests

This paper presents a new approach to designing pseudorandom number generators based on cellular automata. Current cellular automata designs either focus on (i) ensuring desirable sequence properties such as maximum length period, balanced distribution of bits and uniform distribution of n-bit tuples, etc. or (ii) ensuring the generated sequences pass stringent randomness tests. In this work, important design patterns are first identified from the latter approach and then incorporated into cellular automata such that the desirable sequence properties are preserved like in the former approach. Preliminary experiment results show that the new cellular automata designed have potential in passing all DIEHARD tests.

A New Method for Phase Difference Estimation Based on Time-Varying Signal Model

2013 ◽  
Vol 333-335 ◽  
pp. 650-655
Author(s):  
Peng Hui Niu ◽  
Yin Lei Qin ◽  
Shun Ping Qu ◽  
Yang Lou
Keyword(s):  
Signal Processing ◽  
Real Time ◽  
Phase Difference ◽  
Time Signal ◽  
Time Interval ◽  
Time Varying ◽  
Signal Model ◽  
Time Frequency ◽  
Mass Flowmeter ◽  
Coriolis Mass Flowmeter

A new signal processing method for phase difference estimation was proposed based on time-varying signal model, whose frequency, amplitude and phase are time-varying. And then be applied Coriolis mass flowmeter signal. First, a bandpass filtering FIR filter was applied to filter the sensor output signal in order to improve SNR. Then, the signal frequency could be calculated based on short-time frequency estimation. Finally, by short window intercepting, the DTFT algorithm with negative frequency contribution was introduced to calculate the real-time phase difference between two enhanced signals. With the frequency and the phase difference obtained, the time interval of two signals was calculated. Simulation results show that the algorithms studied are efficient. Furthermore, the computation of algorithms studied is simple so that it can be applied to real-time signal processing for Coriolis mass flowmeter.

Computing Phase Shifts of Maximum-Length 90/150 Cellular Automata Sequences

2004 ◽  
pp. 31-39 ◽  
Author(s):  
Sung-Jin Cho ◽  
Un-Sook Choi ◽  
Yoon-Hee Hwang ◽  
Han-Doo Kim ◽  
Yong-Soo Pyo ◽  
...  
Keyword(s):  
Cellular Automata ◽  
Phase Shifts ◽  
Maximum Length

scholarly journals Mesh Phase Analysis of Encased Differential Gear Train for Coaxial Twin-Rotor Helicopter

2019 ◽  
Vol 2019 ◽  
pp. 1-9 ◽  
Author(s):  
Donglin Zhang ◽  
Rupeng Zhu ◽  
Bibo Fu ◽  
Wuzhong Tan
Keyword(s):  
Phase Difference ◽  
Gear Tooth ◽  
Phase Relations ◽  
Gear Train ◽  
Time Varying ◽  
Gear Pair ◽  
Meshing Stiffness ◽  
Differential Gear ◽  
Starting Point ◽  
Twin Rotor

Dynamic excitation caused by time-varying meshing stiffness is one of the most important excitation forms in gear meshing process. The mesh phase relations between each gear pair are an important factor affecting the meshing stiffness. In this paper, the mesh phase relations between gear pairs in an encased differential gear train widely used in coaxial twin-rotor helicopters are discussed. Taking the meshing starting point where the gear tooth enters contact as the reference point, the mesh phase difference between adjacent gear pairs is analyzed and calculated, the system reference gear pair is selected, and the mesh phase difference of each gear pair relative to the system reference gear pair is obtained. The derivation process takes into account the modification of the teeth, the processing, and assembly of the duplicate gears, which makes the calculation method and conclusion more versatile. This work lays a foundation for considering the time-varying meshing stiffness in the study of system dynamics, load distribution, and fault diagnosis of compound planetary gears.

Forecasting Nonlinear Aggregates and Aggregates with Time-varying Weights

2011 ◽  
Vol 231 (1) ◽  
Author(s):  
Helmut Lütkepohl
Keyword(s):  
Fixed Time ◽  
Time Varying ◽  
Nonlinear Functions ◽  
Time Invariant ◽  
Macroeconomic Aggregates

SummaryDespite the fact that many aggregates are nonlinear functions and the aggregation weights of many macroeconomic aggregates are time-varying, much of the literature on forecasting aggregates considers the case of linear aggregates with fixed, time-invariant aggregation weights. In this study a framework for nonlinear contemporaneous aggregation with possibly stochastic or time-varying weights is developed and different predictors for an aggregate are compared theoretically as well as with simulations. Two examples based on European unemployment and inflation series are used to illustrate the virtue of the theoretical setup and the forecasting results.

scholarly journals Cellular automata over generalized Cayley graphs

2017 ◽  
Vol 28 (3) ◽  
pp. 340-383 ◽  
Author(s):  
PABLO ARRIGHI ◽  
SIMON MARTIEL ◽  
VINCENT NESME
Keyword(s):  
Cellular Automata ◽  
Metric Space ◽  
Cayley Graphs ◽  
Continuous Functions ◽  
Point Of View ◽  
Automata Theory ◽  
Time Varying ◽  
Compact Metric Space ◽  
Bounded Degree ◽  
Translation Invariant

It is well-known that cellular automata can be characterized as the set of translation-invariant continuous functions over a compact metric space; this point of view makes it easy to extend their definition from grids to Cayley graphs. Cayley graphs have a number of useful features: the ability to graphically represent finitely generated group elements and their relations; to name all vertices relative to an origin; and the fact that they have a well-defined notion of translation. We propose a notion of graphs, which preserves or generalizes these features. Whereas Cayley graphs are very regular, generalized Cayley graphs are arbitrary, although of a bounded degree. We extend cellular automata theory to these arbitrary, bounded degree, time-varying graphs. The obtained notion of cellular automata is stable under composition and under inversion.

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