Monte Carlo Method, Random Number, and Pseudorandom Number
| AUTHOR | Sugita, Hiroshi |
| PUBLISHER | Mathematical Society of Japan (05/01/2011) |
| PRODUCT TYPE | Paperback (Paperback) |
Description
Although the Monte Carlo method is used in so many fields, its mathematical foundation has been weak until now because of the fundamental problem that a computer cannot generate random numbers. This book presents a strong mathematical formulation of the Monte Carlo method which is based on the theory of random number by Kolmogorov and others and that of pseudorandom number by Blum and others. As a result, we see that the Monte Carlo method may not need random numbers and pseudorandom numbers may suffice. In particular, for the Monte Carlo integration, there exist pseudorandom numbers which serve as complete substitutes for random numbers.Published by Mathematical Society of Japan and distributed by World Scientific Publishing Co. for all markets
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Product Format
Product Details
ISBN-13:
9784931469655
ISBN-10:
4931469655
Binding:
Paperback or Softback (Trade Paperback (Us))
Content Language:
English
More Product Details
Page Count:
148
Carton Quantity:
40
Product Dimensions:
6.80 x 0.40 x 9.70 inches
Weight:
0.65 pound(s)
Feature Codes:
Bibliography
Country of Origin:
SG
Subject Information
BISAC Categories
Mathematics | Number Theory
Mathematics | Physics - Mathematical & Computational
Mathematics | Probability & Statistics - General
Descriptions, Reviews, Etc.
jacket front
Although the Monte Carlo method is used in so many fields, its mathematical foundation has been weak until now because of the fundamental problem that a computer cannot generate random numbers. This book presents a strong mathematical formulation of the Monte Carlo method which is based on the theory of random number by Kolmogorov and others and that of pseudorandom number by Blum and others. As a result, we see that the Monte Carlo method may not need random numbers and pseudorandom numbers may suffice. In particular, for the Monte Carlo integration, there exist pseudorandom numbers which serve as complete substitutes for random numbers.
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publisher marketing
Although the Monte Carlo method is used in so many fields, its mathematical foundation has been weak until now because of the fundamental problem that a computer cannot generate random numbers. This book presents a strong mathematical formulation of the Monte Carlo method which is based on the theory of random number by Kolmogorov and others and that of pseudorandom number by Blum and others. As a result, we see that the Monte Carlo method may not need random numbers and pseudorandom numbers may suffice. In particular, for the Monte Carlo integration, there exist pseudorandom numbers which serve as complete substitutes for random numbers.Published by Mathematical Society of Japan and distributed by World Scientific Publishing Co. for all markets
Show More
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