비만아 부모의 돌봄 경험: q 방법론

After two decades of research and development, elliptic curve cryptography now has widespread exposure and acceptance. Industry, banking, and government standards are in place to facilitate extensive deployment of this efficient public-key mechanism. Anchored by a comprehensive treatment of the practical aspects of elliptic curve cryptography (ECC), this guide explains the basic mathematics, describes state-of-the-art implementation methods, and presents standardized protocols for public-key encryption, digital signatures, and key establishment. In addition, the book addresses some issues that arise in software and hardware implementation, as well as side-channel attacks and countermeasures. Readers receive the theoretical fundamentals as an underpinning for a wealth of practical and accessible knowledge about efficient application. Features & Benefits: * Breadth of coverage and unified, integrated approach to elliptic curve cryptosystems * Describes important industry and government protocols, such as the FIPS 186-2 standard from the U.S. National Institute for Standards and Technology * Provides full exposition on techniques for efficiently implementing finite-field and elliptic curve arithmetic* Distills complex mathematics and algorithms for easy understanding* Includes useful literature references, a list of algorithms, and appendices on sample parameters, ECC standards, and software toolsThis comprehensive, highly focused reference is a useful and indispensable resource for practitioners, professionals, or researchers in computer science, computer engineering, network design, and network data security.

https://cdn.preterhuman.net/texts/cryptography/Hankerson,%20Menezes,%20Vanstone.%20Guide%20to%20elliptic%20curve%20cryptography%20(Springer,%202004)(ISBN%20038795273X)(332s)_CsCr_.pdf

Guide to Elliptic Curve Cryptography

National Institute of Standards and Technology における超伝導研究及び生活

Most of the signal processing that we will study in this course involves local operations on a signal, namely transforming the signal by applying linear combinations of values in the neighborhood of each sample point. You are familiar with such operations from Calculus, namely, taking derivatives and you are also familiar with this from optics namely blurring a signal. We will be looking at sampled signals only. Let's start with a few basic examples. Local difference Suppose we have a 1D image and we take the local difference of intensities, DI(x) = 1 2 (I(x + 1) − I(x − 1)) which give a discrete approximation to a partial derivative. (We compute this for each x in the image.) What is the effect of such a transformation? One key idea is that such a derivative would be useful for marking positions where the intensity changes. Such a change is called an edge. It is important to detect edges in images because they often mark locations at which object properties change. These can include changes in illumination along a surface due to a shadow boundary, or a material (pigment) change, or a change in depth as when one object ends and another begins. The computational problem of finding intensity edges in images is called edge detection. We could look for positions at which DI(x) has a large negative or positive value. Large positive values indicate an edge that goes from low to high intensity, and large negative values indicate an edge that goes from high to low intensity. Example Suppose the image consists of a single (slightly sloped) edge:

http://ieeexplore.ieee.org/iel5/5/31307/01456462.pdf

Linear systems

Ad hoc wireless networks enable new and exciting applications, but also pose significant technical challenges. In this article we give a brief overview of ad hoc wireless networks and their applications with a particular emphasis on energy constraints. We then discuss advances in the link, multiple access, network, and application protocols for these networks. We show that cross-layer design of these protocols is imperative to meet emerging application requirements, particularly when energy is a limited resource.

Design challenges for energy-constrained ad hoc wireless networks

Based on recently published low complexity parallel FIR filter structures, this paper proposes a new scheme to further reduce their hardware complexity. A FIR filter is firstly transformed into linear convolution, which is then implemented by the iterated short convolution algorithm. This linear convolution structure for FIR filter is used as a processing core to implement the subfilters of previously proposed parallel FIR filter structures. A large amount of hardware can be saved by the new scheme. For example, for a 576-tap FIR filter, when the parallelism level changes from 12 to 72, the new scheme can save 1755 to 3375 multiplications at the cost of 21 to 4658 additions and 1516 to 4749 delay elements, respectively.

Further complexity reduction of parallel FIR filters

A joint structural-functional brain network model is presented, which enables the discovery of function-specific brain circuits, and recovers structural connections that are under-estimated by diffusion MRI (dMRI). Incorporating information from functional MRI (fMRI) into diffusion MRI to estimate brain circuits is a challenging task. Usually, seed regions for tractography are selected from fMRI activation maps to extract the white matter pathways of interest. The proposed method jointly analyzes whole brain dMRI and fMRI data, allowing the estimation of complete function-specific structural networks instead of interactively investigating the connectivity of individual cortical/sub-cortical areas. Additionally, tractography techniques are prone to limitations, which can result in erroneous pathways. The proposed framework explicitly models the interactions between structural and functional connectivity measures thereby improving anatomical circuit estimation. Results on Human Connectome Project (HCP) data demonstrate the benefits of the approach by successfully identifying function-specific anatomical circuits, such as the language and resting-state networks. In contrast to correlation-based or independent component analysis (ICA) functional connectivity mapping, detailed anatomical connectivity patterns are revealed for each functional module. Results on a phantom (Fibercup) also indicate improvements in structural connectivity mapping by rejecting false-positive connections with insufficient support from fMRI, and enhancing under-estimated connectivity with strong functional correlation.

/pdf/function-specific-and-enhanced-brain-structural-connectivity-414i8qv26l.pdf

Function-specific and Enhanced Brain Structural Connectivity Mapping via Joint Modeling of Diffusion and Functional MRI

Pipelined and parallel architectures for high-speed implementation of Huffman and Viterbi decoders (both of which belong to the class of tree-based decoders) are presented. Huffman decoders are used for lossless compression. The Viterbi decoder is commonly used in communications systems. The achievable speed in these decoders is inherently limited due to the sequential nature of their computation. This speed limitation is overcome using a previously proposed technique of look-ahead computation. The incremental computation technique is used to obtain efficient parallel (or block) implementations. The decomposition technique is exploited to reduce the hardware complexity in pipelined Viterbi decoders, but not in Huffman decoders. Logic minimization is used to reduce the hardware overhead complexity in pipelined Huffman decoders. >

High-speed VLSI architectures for Huffman and Viterbi decoders

The design of high-speed architectures is addressed for fixed-point, two's-complement, bit-parallel, pipelined, multiplication, division and square-root operations. The architectures presented make use of hybrid number representations (i.e. the input and output numbers are presented using two's complement representation, and the internal numbers are represented using radix-2 redundant representation). A fast, new conversion scheme for converting radix-2 redundant numbers to two's-complement binary numbers is presented, and this is used to design a reduced latency bit-parallel multiplier. The novel sign-multiplexing scheme helps detect the sign of a redundant number very quickly and is used in combination with the remainder conditioning scheme to achieve very high speed in fixed-point division and square-root operators. These architectures require fewer pipelining latches than their conventional two's-complement counterparts. Reduction in latency without sacrificing clock speed has resulted in reduced computation time for these operations. >

High-speed VLSI arithmetic processor architectures using hybrid number representation

Because of their excellent error-correcting performance, low-density parity-check (LDPC) codes have recently attracted a lot of attention. In this paper, we are interested in the practical LDPC code decoder hardware implementations. The direct fully parallel decoder implementation usually incurs too high hardware complexity for many real applications, thus partly parallel decoder design approaches that can achieve appropriate trade-offs between hardware complexity and decoding throughput are highly desirable. Applying a joint code and decoder design methodology, we develop a high-speed (3, k)-regular LDPC code partly parallel decoder architecture based on which we implement a 9216-bit, rate-1/2 (3, 6)-regular LDPC code decoder on Xilinx FPGA device. This partly parallel decoder supports a maximum symbol throughput of 54 Mbps and achieves BER 10-6 at 2 dB over AWGN channel while performing maximum 18 decoding iterations.

/pdf/an-fpga-implementation-of-3-6-regular-low-density-parity-2w0imn5z9u.pdf

Keshab K. Parhi

Papers

Further complexity reduction of parallel FIR filters

Function-specific and Enhanced Brain Structural Connectivity Mapping via Joint Modeling of Diffusion and Functional MRI

High-speed VLSI architectures for Huffman and Viterbi decoders

High-speed VLSI arithmetic processor architectures using hybrid number representation

An FPGA implementation of (3, 6)-regular low-density parity-check code decoder