Ronald T. Kneusel holds a PhD in Computer Science from the University of Colorado, Boulder and an MS in Physics from Michigan State University. His background includes development of algorithms and applications for varied scientific disciplines from remote sensing to medical imaging. He is currently a Senior Data Scientist for Harris Corporation applying deep learning models to remote sensing imagery and other data sources. A product of the microcomputer revolution, Kneusel has had a life-long fascination with all aspects of computer science and mathematics. This is his second Springer book. The first, “Numbers and Computers” (in 2nd edition), explores how computers store and manipulate numbers.

• 1 Random and Pseudorandom Sequences.- 2 Generating Uniform Random Numbers.- 3 Generating Nonuniform Random Numbers.- 4 Testing Pseudorandom Generators.- 5 Parallel Random Number Generators.- 6 Cryptographically Secure Pseudorandom Number Generators.- 7 Other Random Sequences.

Ronald T. Kneusel holds a PhD in Computer Science from the University of Colorado, Boulder and an MS in Physics from Michigan State University. His background includes development of algorithms and applications for varied scientific disciplines from remote sensing to medical imaging. He is currently a Senior Data Scientist for Harris Corporation applying deep learning models to remote sensing imagery and other data sources. A product of the microcomputer revolution, Kneusel has had a life-long fascination with all aspects of computer science and mathematics. This is his second Springer book. The first, “Numbers and Computers” (in 2nd edition), explores how computers store and manipulate numbers.

• 1 Random and Pseudorandom Sequences.- 2 Generating Uniform Random Numbers.- 3 Generating Nonuniform Random Numbers.- 4 Testing Pseudorandom Generators.- 5 Parallel Random Number Generators.- 6 Cryptographically Secure Pseudorandom Number Generators.- 7 Other Random Sequences.

Ronald T. Kneusel holds a PhD in Computer Science from the University of Colorado, Boulder and an MS in Physics from Michigan State University. His background includes development of algorithms and applications for varied scientific disciplines from remote sensing to medical imaging. He is currently a Senior Data Scientist for Harris Corporation applying deep learning models to remote sensing imagery and other data sources. A product of the microcomputer revolution, Kneusel has had a life-long fascination with all aspects of computer science and mathematics. This is his second Springer book. The first, “Numbers and Computers” (in 2nd edition), explores how computers store and manipulate numbers.

• 1 Random and Pseudorandom Sequences.- 2 Generating Uniform Random Numbers.- 3 Generating Nonuniform Random Numbers.- 4 Testing Pseudorandom Generators.- 5 Parallel Random Number Generators.- 6 Cryptographically Secure Pseudorandom Number Generators.- 7 Other Random Sequences.