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Energy Minimization Using Multiple Supply Voltages*
Energy Minimization Using Multiple Supply Voltages*

Full text
Full text

... On the other hand, in Theorem 1 we showed that the unaugmented array contains each positive integer exactly once. Therefore, for k >_ 2, every positive integer occurs at least k - 1 times in {b^k\}. From ax - 1 > 1/2, we know that any integer can occur at most twice in the sequence {f± (n) - n}. The ...
Multiple-Choice Random Network for Server Load
Multiple-Choice Random Network for Server Load

... i = 1, 2, . . . , e, ae−i is changed into be−i if they are not the same. This is known as prefix routing. As an example, suppose m = n = 25 , and suppose node 10110 makes a query for file 00000, which resides in node 00000. A possible route in a Plaxton network may consist of the following sequence ...
A solution method for general contact±impact problems - Z
A solution method for general contact±impact problems - Z

... Aftre the contact takes place, a constraint arises. That is, the contactor node must not penetrate the target surface. A mathematical form of this constraint is the function F in Eq. (11) for in®nitesimal incremental displacements. The problem is how to impose Eq. (11) to the motion of the system. I ...
Assignment 8
Assignment 8

(Riemann) Integration Sucks!!!
(Riemann) Integration Sucks!!!

... (This is also a little bit misleading, since there are also a lot rational numbers, but it illustrates the point I’m going to make). So looking at this second picture, even though f is not Riemann integrable, we would still like to say ”The area under its graph is 1”. This is because, on [0, 1], f ...
PowerPoint 簡報 - National Cheng Kung University
PowerPoint 簡報 - National Cheng Kung University

... The second step of TUF converts the leaves of the BDD into instances of a ternary data structure (tries, nested tries, and TCAM classifiers.). The third step, the core of TUF, merges these ternary data structures to form ternary data structures that encode larger sections of the input space. ...
MKJT 90 300/500 V (H05V2-K)
MKJT 90 300/500 V (H05V2-K)

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Syntactic Codes and Grammar Refinement

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3-D Graph Processor

... 2-D and 3-D links have same bit rate and similar power consumption Power consumption is dominated by frequency multiplication and phase locking for which 2-D and 3-D links use common circuitry ...
Optical Burst Switching
Optical Burst Switching

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Binary Integer Programming in associative data models

... active and thus which data to be marked as green, white or grey. If you qlick (classic Qlikpun for "click") on a post, it will turn green and the engine will infer what other values are to be colored white or grey. The inference is possible due to the QIX engine storing the data in an associative mo ...
Substitution and Evaluation
Substitution and Evaluation

Data Discretization
Data Discretization

ICDM07_Jin - Kent State University
ICDM07_Jin - Kent State University

A Functional Approach to the Observer Pattern
A Functional Approach to the Observer Pattern

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Search - Temple University

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PPT
PPT

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Parallel Prefix

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Mining Sensor Data Streams

Graphing Skills 1 - Scott County Schools
Graphing Skills 1 - Scott County Schools

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Look before you loop

... ' regular ASCII characters destLang.Value = 0 End Select ' Convert the Notes characters to the desired character code set for English or Japanese, ' and copy that data into the BLOB field (which does not convert them further because ' BLOBS don't have character sets associated with them). Call destF ...
Hierarchy in lexical organisation of natural
Hierarchy in lexical organisation of natural

Development of Readout ASIC for FPCCD Vertex Detector
Development of Readout ASIC for FPCCD Vertex Detector

... slow(~10kbps) ⇒ ~260,000pix • Speed transmission of VME module to PC is slow. • ADC output is temporarily stored in FIFO. • By limit of FPGA capacity, all the data cannot be stored. ➫ ADC data were converted to 1bit. – Threshold : 30 ...
Lexical graphs - Hal-SHS
Lexical graphs - Hal-SHS

< 1 ... 25 26 27 28 29 30 31 32 33 ... 124 >

Corecursion

In computer science, corecursion is a type of operation that is dual to recursion. Whereas recursion works analytically, starting on data further from a base case and breaking it down into smaller data and repeating until one reaches a base case, corecursion works synthetically, starting from a base case and building it up, iteratively producing data further removed from a base case. Put simply, corecursive algorithms use the data that they themselves produce, bit by bit, as they become available, and needed, to produce further bits of data. A similar but distinct concept is generative recursion which may lack a definite ""direction"" inherent in corecursion and recursion. Where recursion allows programs to operate on arbitrarily complex data, so long as they can be reduced to simple data (base cases), corecursion allows programs to produce arbitrarily complex and potentially infinite data structures, such as streams, so long as it can be produced from simple data (base cases). Where recursion may not terminate, never reaching a base state, corecursion starts from a base state, and thus produces subsequent steps deterministically, though it may proceed indefinitely (and thus not terminate under strict evaluation), or it may consume more than it produces and thus become non-productive. Many functions that are traditionally analyzed as recursive can alternatively, and arguably more naturally, be interpreted as corecursive functions that are terminated at a given stage, for example recurrence relations such as the factorial.Corecursion can produce both finite and infinite data structures as result, and may employ self-referential data structures. Corecursion is often used in conjunction with lazy evaluation, to only produce a finite subset of a potentially infinite structure (rather than trying to produce an entire infinite structure at once). Corecursion is a particularly important concept in functional programming, where corecursion and codata allow total languages to work with infinite data structures.
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