Random sequential coding by Hamming distance

1986 ◽  
Vol 23 (03) ◽  
pp. 688-695 ◽  
Author(s):  
Yoshiaki Itoh ◽  
Herbert Solomon
Keyword(s):  
Computer Simulations ◽  
Packing Density ◽  
Hamming Distance ◽  
Random Packing ◽  
Empirical Constant ◽  
Simple Cubic ◽  
Simulation Results ◽  
Simple Models

Here we introduce two simple models: simple cubic random packing and random packing by Hamming distance. Consider the packing density γ d of dimension d by cubic random packing. From computer simulations up to dimension 11, γ d +1/γ d seems to approach 1. Also, we give simulation results for random packing by Hamming distance and discuss the behavior of packing density when dimensionality is increased. For the case of Hamming distances of 2 or 3, d–α fits the simulation results of packing density where α is an empirical constant. The variance of packing density is larger when k is even and smaller when k is odd, where k represents Hamming distance.

Random sequential coding by Hamming distance

1986 ◽  
Vol 23 (3) ◽  
pp. 688-695 ◽  
Author(s):  
Yoshiaki Itoh ◽  
Herbert Solomon
Keyword(s):  
Computer Simulations ◽  
Packing Density ◽  
Hamming Distance ◽  
Random Packing ◽  
Empirical Constant ◽  
Simple Cubic ◽  
Simulation Results ◽  
Simple Models

Here we introduce two simple models: simple cubic random packing and random packing by Hamming distance. Consider the packing density γ d of dimension d by cubic random packing. From computer simulations up to dimension 11, γ d+1/γ d seems to approach 1. Also, we give simulation results for random packing by Hamming distance and discuss the behavior of packing density when dimensionality is increased. For the case of Hamming distances of 2 or 3, d–α fits the simulation results of packing density where α is an empirical constant. The variance of packing density is larger when k is even and smaller when k is odd, where k represents Hamming distance.

Packing densities of randomly constructed codes

1989 ◽  
Vol 26 (03) ◽  
pp. 512-523
Author(s):  
Clifton Sutton
Keyword(s):  
Linear Regression ◽  
Asymptotic Approximation ◽  
Hamming Distance ◽  
Random Packing ◽  
Approximation Formula ◽  
Empirical Constant ◽  
Non Linear ◽  
Packing Densities

Codes having all pairs of words separated by a Hamming distance of at least d are stochastically constructed by sequentially packing randomly generated q-ary n-tuples. Estimates of the random packing densities are obtained by repeated simulation. Using non-linear regression to fit the estimated densities, an asymptotic approximation formula is obtained for the packing densities which depends only on q, n, d, and an empirical constant.

Packing densities of randomly constructed codes

1989 ◽  
Vol 26 (3) ◽  
pp. 512-523
Author(s):  
Clifton Sutton
Keyword(s):  
Linear Regression ◽  
Asymptotic Approximation ◽  
Hamming Distance ◽  
Random Packing ◽  
Approximation Formula ◽  
Empirical Constant ◽  
Non Linear ◽  
Packing Densities

Codes having all pairs of words separated by a Hamming distance of at least d are stochastically constructed by sequentially packing randomly generated q-ary n-tuples. Estimates of the random packing densities are obtained by repeated simulation. Using non-linear regression to fit the estimated densities, an asymptotic approximation formula is obtained for the packing densities which depends only on q, n, d, and an empirical constant.

Computer Simulation of an Synthetic Ultraviolet Absorbent in the Interface of DMB and DMF

2010 ◽  
Vol 146-147 ◽  
pp. 966-971
Author(s):  
Qi Hua Jiang ◽  
Hai Dong Zhang ◽  
Bin Xiang ◽  
Hai Yun He ◽  
Ping Deng
Keyword(s):  
Computer Simulation ◽  
Computer Simulations ◽  
Density Functional ◽  
Density Functional Method ◽  
Mean Field ◽  
Functional Method ◽  
Dynamic Density ◽  
Interface Phase ◽  
Simulation Results

This work studies the aggregation of an synthetic ultraviolet absorbent, named 2-hydroxy-4-perfluoroheptanoate-benzophenone (HPFHBP), in the interface between two solvents which can not completely dissolve each other. The aggregation is studied by computer simulations based on a dynamic density functional method and mean-field interactions, which are implemented in the MesoDyn module and Blend module of Material Studios. The simulation results show that the synthetic ultraviolet absorbent diffuse to the interface phase and the concentration in the interface phase is greater than it in the solvents phase.

scholarly journals Quaternary regenerative CMOS logic circuits with high-impedance output state

2005 ◽  
Vol 18 (3) ◽  
pp. 505-514
Author(s):  
Dusanka Bundalo ◽  
Branimir Ðordjevic ◽  
Zlatko Bundalo
Keyword(s):  
Computer Simulation ◽  
Computer Simulations ◽  
Delay Time ◽  
Propagation Delay ◽  
Logic Circuits ◽  
Output State ◽  
High Impedance ◽  
Multiple Valued Logic ◽  
Propagation Delay Time ◽  
Simulation Results

Principles and possibilities of synthesis and design of quaternary multiple valued regenerative CMOS logic circuits with high-impedance output state are de- scribed and proposed in the paper. Two principles of synthesis and implementation of CMOS regenerative quaternary multiple-valued logic circuits with high-impedance output state are proposed and described: the simple circuits with smaller number of transistors, and the buffer/driver circuits with decreased propagation delay time. The schemes of such logic circuits are given and analyzed by computer simulations. Some of computer simulation results confirming descriptions and conclusions are also given in the paper.

Computation of Madalines' Sensitivity to Input and Weight Perturbations

2006 ◽  
Vol 18 (11) ◽  
pp. 2854-2877 ◽  
Author(s):  
Yingfeng Wang ◽  
Xiaoqin Zeng ◽  
Daniel So Yeung ◽  
Zhihang Peng
Keyword(s):  
Probability Theory ◽  
Computer Simulations ◽  
Structural Characteristics ◽  
Analytical Formula ◽  
Single Neurons ◽  
Important Measure ◽  
Simulation Results ◽  
Theoretical Results ◽  
Good Agreement

The sensitivity of a neural network's output to its input and weight perturbations is an important measure for evaluating the network's performance. In this letter, we propose an approach to quantify the sensitivity of Madalines. The sensitivity is defined as the probability of output deviation due to input and weight perturbations with respect to overall input patterns. Based on the structural characteristics of Madalines, a bottomup strategy is followed, along which the sensitivity of single neurons, that is, Adalines, is considered first and then the sensitivity of the entire Madaline network. Bymeans of probability theory, an analytical formula is derived for the calculation of Adalines' sensitivity, and an algorithm is designed for the computation of Madalines' sensitivity. Computer simulations are run to verify the effectiveness of the formula and algorithm. The simulation results are in good agreement with the theoretical results.

The random packing of fibres in three dimensions

1995 ◽  
Vol 451 (1943) ◽  
pp. 737-746 ◽  
Keyword(s):  
Packing Density ◽  
Volume Fraction ◽  
Random Packing ◽  
Experimental Results ◽  
Three Dimensions ◽  
Approximate Relationship

An investigation has been carried out of the limiting packing density of an array of long straight rigid fibres distributed randomly in space as a function of the length of the fibre. We derive an approximate relationship between the limiting volume fraction V f and the slenderness λ of the fibres defined as length divided by diameter. The formula agrees well with our experimental results and those found in the literature.

Statistical geometrical approach to random packing density of equal spheres

Nature ◽  
1974 ◽  
Vol 252 (5480) ◽  
pp. 202-205 ◽  
Author(s):  
Keishi Gotoh ◽  
John L. Finney
Keyword(s):  
Packing Density ◽  
Random Packing ◽  
Geometrical Approach

Swarming Algorithm for Unmanned Aerial Vehicle (UAV) Quadrotors – Swarm Behavior for Aggregation, Foraging, Formation, and Tracking –

2014 ◽  
Vol 18 (5) ◽  
pp. 745-751 ◽  
Author(s):  
Argel A. Bandala ◽  
◽  
Elmer P. Dadios ◽  
Ryan Rhay P. Vicerra ◽  
Laurence A. Gan Lim
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Computer Simulations ◽  
Group Performance ◽  
Robotic System ◽  
Robot Swarms ◽  
Average Accuracy ◽  
Swarm Behavior ◽  
Aerial Vehicle ◽  
Simulation Results ◽  
Robotic Agent

This paper presents the fusion of swarm behavior in multi robotic system specifically the quadrotors unmanned aerial vehicle (QUAV) operations. This study directed on using robot swarms because of its key feature of decentralized processing amongst its member. This characteristic leads to advantages of robot operations because an individual robot failure will not affect the group performance. The algorithm emulating the animal or insect swarm behaviors is presented in this paper and implemented into an artificial robotic agent (QUAV) in computer simulations. The simulation results concluded that for increasing number of QUAV the aggregation accuracy increases with an accuracy of 90.62%. The experiment for foraging revealed that the number of QUAV does not affect the accuracy of the swarm instead the iterations needed are greatly improved with an average of 160.53 iterations from 50 to 500 QUAV. For swarm tracking, the average accuracy is 89.23%. The accuracy of the swarm formation is 84.65%. These results clearly defined that the swarm system is accurate enough to perform the tasks and robust in any QUAV number.

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