Results 261 to 270 of about 289,909 (310)
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Fuzzy Sets and Systems, 2016
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
M. Saheli, S. Khajepour Gelousalar
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zbMATH Open Web Interface contents unavailable due to conflicting licenses.
M. Saheli, S. Khajepour Gelousalar
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On vectorial inner product spaces [PDF]
Czechoslovak Mathematical Journal, 2000 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Marques, João de Deus
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IEEE Transactions on Computers, 1978
The inner product computer is a special-purpose computational unit intended to be used as an adjunct to a general-purpose digital computer to perform numerical processing tasks which previously exceeded the capacity of the general-purpose computer. The algorithmic structure of the inner product is briefly reviewed in the first section of this paper ...
Earl E. Swartzlander Jr. +2 more
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The inner product computer is a special-purpose computational unit intended to be used as an adjunct to a general-purpose digital computer to perform numerical processing tasks which previously exceeded the capacity of the general-purpose computer. The algorithmic structure of the inner product is briefly reviewed in the first section of this paper ...
Earl E. Swartzlander Jr. +2 more
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Inner Product Groups and Riesz Representation Theorem
Symmetry, 2021 In this paper, we introduce an inner product on abelian groups and, after investigating the basic properties of the inner product, we first show that each inner product group is a torsion-free abelian normed group.
Alireza Pourmoslemi, Mehdi Salimi
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Microprocessing and Microprogramming, 1987
Abstract The inner Product Processor (IPP) is designed to increase the computing power of a Multiple Instruction stream Multiple Data stream (MIMD) supercomputer, the Delft Parallel Processor (DPP). At this moment a small MIMD supercomputer with 16 Processing Elements (PE's) has been realized.
Edward E. E. Frietman, F. Bruggeman
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Abstract The inner Product Processor (IPP) is designed to increase the computing power of a Multiple Instruction stream Multiple Data stream (MIMD) supercomputer, the Delft Parallel Processor (DPP). At this moment a small MIMD supercomputer with 16 Processing Elements (PE's) has been realized.
Edward E. E. Frietman, F. Bruggeman
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SIAM Journal on Mathematical Analysis, 1973
A fundamental inequality which provides lower bounds for real-valued inner products is stated and proved.
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A fundamental inequality which provides lower bounds for real-valued inner products is stated and proved.
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Numerical Linear Algebra with Applications, 2004
AbstractGiven the operator product BA in which both A and B are symmetric positive‐definite operators, for which symmetric positive‐definite operators C is BA symmetric positive‐definite in the C inner product 〈x, y〉C? This question arises naturally in preconditioned iterative solution methods, and will be answered completely here.
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AbstractGiven the operator product BA in which both A and B are symmetric positive‐definite operators, for which symmetric positive‐definite operators C is BA symmetric positive‐definite in the C inner product 〈x, y〉C? This question arises naturally in preconditioned iterative solution methods, and will be answered completely here.
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On Winograd's Algorithm for Inner Products
IEEE Transactions on Computers, 1970This correspondence demonstrates an improvement on Winogard's algorithm for inner products as applied to the multiplication of two matrices.
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A VLSI inner product macrocell
IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 1998Microcontrollers for embedded computer applications require a library of dedicated macrocells for specific applications. Arithmetic and basic DSP computations may be too inefficient when computed by software on the core CPU of the microcontroller. The architecture of a VLSI macrocell, for the ST9 microcontroller (8 bit), dedicated to the computation of
BREVEGLIERI, LUCA ODDONE, DADDA, LUIGI
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A New Algorithm for Inner Product
IEEE Transactions on Computers, 1968Abstract—In this note we describe a new way of computing the inner product of two vectors. This method cuts down the number of multiplications required when we want to perform a large number of inner products on a smaller set of vectors. In particular, we obtain that the product of two n×n matrices can be performed using roughly n3/2 multiplications ...
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