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using State Encoding Techniques
"... Abstract: In present days, there is a need for ever increasing high performance and low power devices, these devices need to meet performance constraints like speed, area & power. This paper describes the area and speed constraints of a 16 bit processor with the implementation of three state enc ..."
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encoding techniques binary, one hot & gray coding technique. The processor architecture is designed using Verilog HDL, simulated on Modelsim and synthesized on Precision RTL synthesis tool & on XILINX ISE 12.1 for the Spartan3E FPGA. From the synthesis reports it is observed that Onehot encoding
On Encoding Techniques Definition
"... A SemiThue system S over Σ is a finite set of rewriting rules {u1 → v1, u2 → v2,..., un → vn}. Derivation in S is a sequence of words w1, w2, w3... over Σ so that for each k, there exists rule ui → vi, and wk = pkui sk and wk+1 = pkvi sk. Turing Machine vs. SemiThue systems Turing machine → SemiT ..."
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A SemiThue system S over Σ is a finite set of rewriting rules {u1 → v1, u2 → v2,..., un → vn}. Derivation in S is a sequence of words w1, w2, w3... over Σ so that for each k, there exists rule ui → vi, and wk = pkui sk and wk+1 = pkvi sk. Turing Machine vs. SemiThue systems Turing machine → SemiThue system SemiThue system → Turing machine
LowPower Instruction Encoding Techniques
"... We describe low power instruction encoding techniques for lowpower instruction fetches. Instruction fields of a binary program are reencoded so that the number of bits switched from the neighboring fields of consecutive instructions is minimized. The lowpower encoding techniques are applied into ..."
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Cited by 6 (0 self)
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We describe low power instruction encoding techniques for lowpower instruction fetches. Instruction fields of a binary program are reencoded so that the number of bits switched from the neighboring fields of consecutive instructions is minimized. The lowpower encoding techniques are applied
Instruction Encoding Techniques for Area Minimization of
 Instruction ROM. International Symposium on System Synthesis
, 1998
"... In this paper, we propose instruction encoding techniques for embedded system design, which encode immediate fields of instructions to reduce the size of an instruction memory. Although our proposed techniques require an additional decoder for the encoded immediate values, experimental results d ..."
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Cited by 3 (0 self)
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In this paper, we propose instruction encoding techniques for embedded system design, which encode immediate fields of instructions to reduce the size of an instruction memory. Although our proposed techniques require an additional decoder for the encoded immediate values, experimental results
Lowpower bus encoding techniques
 IST200030093/EASY PROJECT, DOC. ID: EASY/WP3/ POLITO/DL/P/D17/B1
, 2002
"... This deliverable evaluates the applicability of encoding techniques in the context of the design of lowpower communication buses. The existing literature is reviewed in detail with the purpose of identifying the classes of bus encoding schemes that are most suitable to the EASY project, namely, th ..."
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Cited by 1 (1 self)
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This deliverable evaluates the applicability of encoding techniques in the context of the design of lowpower communication buses. The existing literature is reviewed in detail with the purpose of identifying the classes of bus encoding schemes that are most suitable to the EASY project, namely
The Laplacian Pyramid as a Compact Image Code
, 1983
"... We describe a technique for image encoding in which local operators of many scales but identical shape serve as the basis functions. The representation differs from established techniques in that the code elements are localized in spatial frequency as well as in space. Pixeltopixel correlations a ..."
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Cited by 1388 (12 self)
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We describe a technique for image encoding in which local operators of many scales but identical shape serve as the basis functions. The representation differs from established techniques in that the code elements are localized in spatial frequency as well as in space. Pixeltopixel correlations
Learning the Kernel Matrix with SemiDefinite Programming
, 2002
"... Kernelbased learning algorithms work by embedding the data into a Euclidean space, and then searching for linear relations among the embedded data points. The embedding is performed implicitly, by specifying the inner products between each pair of points in the embedding space. This information ..."
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Cited by 775 (21 self)
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is contained in the socalled kernel matrix, a symmetric and positive definite matrix that encodes the relative positions of all points. Specifying this matrix amounts to specifying the geometry of the embedding space and inducing a notion of similarity in the input spaceclassical model selection
Text Chunking using TransformationBased Learning
, 1995
"... Eric Brill introduced transformationbased learning and showed that it can do partofspeech tagging with fairly high accuracy. The same method can be applied at a higher level of textual interpretation for locating chunks in the tagged text, including nonrecursive "baseNP" chunks. For ..."
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Cited by 523 (0 self)
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. For this purpose, it is convenient to view chunking as a tagging problem by encoding the chunk structure in new tags attached to each word. In automatic tests using Treebankderived data, this technique achieved recall and precision rates of roughly 92% for baseNP chunks and 88% for somewhat more complex chunks
Results 1  10
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