When Least Is Best: How Mathematicians Discovered Many Clever Ways to Make Things as Small (or as Large) as Possible - Tapa dura

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Paul J. Nahin is Professor of Electrical Engineering at the University of New Hampshire. He is the author of many books, including the bestselling "An Imaginary Tale: The Story of the Square Root of Minus One" and "Duelling Idiots and Other Probability Puzzlers" (both Princeton).

De la contraportada

"This is a delightful account of how the concepts of maxima, minima, and differentiation evolved with time. The level of mathematical sophistication is neither abstract nor superficial and it should appeal to a wide audience."--Ali H. Sayed, University of California, Los Angeles

"When Least Is Best is an illustrative historical walk through optimization problems as solved by mathematicians and scientists. Although many of us associate solving optimization with calculus, Paul J. Nahin shows here that many key problems were posed and solved long before calculus was developed."--Mary Ann B. Freeman, Math Team Development Manager, Mathworks

De la solapa interior

"This is a delightful account of how the concepts of maxima, minima, and differentiation evolved with time. The level of mathematical sophistication is neither abstract nor superficial and it should appeal to a wide audience."--Ali H. Sayed, University of California, Los Angeles

"When Least Is Best is an illustrative historical walk through optimization problems as solved by mathematicians and scientists. Although many of us associate solving optimization with calculus, Paul J. Nahin shows here that many key problems were posed and solved long before calculus was developed."--Mary Ann B. Freeman, Math Team Development Manager, Mathworks