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The first column of an interspersion
 Fib. Quart
, 1994
"... In 1977, K B. Stolarsky [9] introduced an array of positive integers whose first row consists of the Fibonacci numbers {Fn:«>2}:1 2 3 5 8 13.... The subsequent rows are "generalized Fibonacci sequences. " In fact, much more is true. The rows of the array are, in a sense, the set of all ..."
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Cited by 1 (0 self)
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In 1977, K B. Stolarsky [9] introduced an array of positive integers whose first row consists of the Fibonacci numbers {Fn:«>2}:1 2 3 5 8 13.... The subsequent rows are "generalized Fibonacci sequences. " In fact, much more is true. The rows of the array are, in a sense, the set of all
Stable signal recovery from incomplete and inaccurate measurements,”
 Comm. Pure Appl. Math.,
, 2006
"... Abstract Suppose we wish to recover a vector x 0 ∈ R m (e.g., a digital signal or image) from incomplete and contaminated observations y = Ax 0 + e; A is an n × m matrix with far fewer rows than columns (n m) and e is an error term. Is it possible to recover x 0 accurately based on the data y? To r ..."
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Cited by 1397 (38 self)
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? To recover x 0 , we consider the solution x to the 1 regularization problem where is the size of the error term e. We show that if A obeys a uniform uncertainty principle (with unitnormed columns) and if the vector x 0 is sufficiently sparse, then the solution is within the noise level As a first example
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"... I am honored to be writing my first column as Chair of the APPIC Board, and want to start by highlighting the current and immediate past Board members who make significant contributions to the work of APPIC every day! Most importantly, I want to thank Steve McCutcheon who has served in this role fo ..."
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I am honored to be writing my first column as Chair of the APPIC Board, and want to start by highlighting the current and immediate past Board members who make significant contributions to the work of APPIC every day! Most importantly, I want to thank Steve McCutcheon who has served in this role
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"... Evaluation of first mode of vibration, base fixidity, and frequency effects in resonant ..."
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Evaluation of first mode of vibration, base fixidity, and frequency effects in resonant
A finitevolume, incompressible Navier–Stokes model for studies of the ocean on parallel computers.
 J. Geophys. Res.,
, 1997
"... Abstract. The numerical implementation of an ocean model based on the incompressible Navier Stokes equations which is designed for studies of the ocean circulation on horizontal scales less than the depth of the ocean right up to global scale is described. A "pressure correction" method i ..."
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Cited by 293 (32 self)
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field is separated into surface, hydrostatic, and nonhydrostatic components. First, as in hydrostatic models, a twodimensional problem is inverted for the surface pressure which is then made use of in the threedimensional inversion for the nonhydrostatic pressure. Preconditioned conjugate
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"... John Lithgow, a versatile and awardwinning actor of the stage, screen, and television, is also a bestselling author of children’s books. Music and the Arts are pervasive topics in Lithgow’s books. His first book, The Remarkable Farkle McBride (Lithgow & Payne, 2000) tells the story of a boy w ..."
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John Lithgow, a versatile and awardwinning actor of the stage, screen, and television, is also a bestselling author of children’s books. Music and the Arts are pervasive topics in Lithgow’s books. His first book, The Remarkable Farkle McBride (Lithgow & Payne, 2000) tells the story of a boy
Multicolumn deep neural networks for image classification
 IN PROCEEDINGS OF THE 25TH IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2012
, 2012
"... Traditional methods of computer vision and machine learning cannot match human performance on tasks such as the recognition of handwritten digits or traffic signs. Our biologically plausible deep artificial neural network architectures can. Small (often minimal) receptive fields of convolutional win ..."
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Cited by 151 (9 self)
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winnertakeall neurons yield large network depth, resulting in roughly as many sparsely connected neural layers as found in mammals between retina and visual cortex. Only winner neurons are trained. Several deep neural columns become experts on inputs preprocessed in different ways; their predictions
Memory Access Scheduling
, 2000
"... The bandwidth and latency of a memory system are strongly dependent on the manner in which accesses interact with the "3D" structure of banks, rows, and columns characteristic of contemporary DRAM chips. There is nearly an order of magnitude difference in bandwidth between successive refe ..."
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Cited by 206 (10 self)
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The bandwidth and latency of a memory system are strongly dependent on the manner in which accesses interact with the "3D" structure of banks, rows, and columns characteristic of contemporary DRAM chips. There is nearly an order of magnitude difference in bandwidth between successive
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