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wyszukanych pozycji: 3
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Prolate Spheroidal Wave Functions of Order Zero: Mathematical Tools for Bandlimited Approximation
ISBN: 9781489978653 / Angielski / Miękka / 2016 / 379 str. Termin realizacji zamówienia: ok. 22 dni roboczych (Dostawa w 2026 r.) Prolate Spheroidal Wave Functions (PSWFs) are the eigenfunctions of the bandlimited operator in one dimension. As such, they play an important role in signal processing, Fourier analysis, and approximation theory. While historically the numerical evaluation of PSWFs presented serious difficulties, the developments of the last fifteen years or so made them as computationally tractable as any other class of special functions. As a result, PSWFs have been becoming a popular computational tool. The present book serves as a complete, self-contained resource for both theory and... Prolate Spheroidal Wave Functions (PSWFs) are the eigenfunctions of the bandlimited operator in one dimension. As such, they play an important role... |
cena:
401,58 |
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Prolate Spheroidal Wave Functions of Order Zero: Mathematical Tools for Bandlimited Approximation
ISBN: 9781461482581 / Angielski / Twarda / 2013 / 379 str. Termin realizacji zamówienia: ok. 22 dni roboczych (Dostawa w 2026 r.) Prolate Spheroidal Wave Functions (PSWFs) are the eigenfunctions of the bandlimited operator in one dimension. As such, they play an important role in signal processing, Fourier analysis, and approximation theory. While historically the numerical evaluation of PSWFs presented serious difficulties, the developments of the last fifteen years or so made them as computationally tractable as any other class of special functions. As a result, PSWFs have been becoming a popular computational tool. The present book serves as a complete, self-contained resource for both theory and... Prolate Spheroidal Wave Functions (PSWFs) are the eigenfunctions of the bandlimited operator in one dimension. As such, they play an important role... |
cena:
401,58 |
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A Randomized Approximate Nearest Neighbors Algorithm
ISBN: 9783659128387 / Angielski / Miękka / 2012 / 136 str. Termin realizacji zamówienia: ok. 10-14 dni roboczych (Dostawa w 2026 r.) The classical nearest neighbors problem is formulated as follows: given a collection of N points in the Euclidean space R^d, for each point, find its k nearest neighbors (i.e. closest points). Obviously, for each point X, one can compute the distances from X to every other point, and then find k shortest distances in the resulting array. However, the computational cost of this naive approach is at least (d*N^2)/2 operations, which is prohibitively expensive in many applications. For example, "naively" solving the nearest neighbors problem with d=100, N=1,000,000 and k=30 on a modern laptop...
The classical nearest neighbors problem is formulated as follows: given a collection of N points in the Euclidean space R^d, for each point, find its ...
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cena:
263,29 |
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