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

This paper presents a novel approach to develop pipelined fast Fourier transform (FFT) architectures for real-valued signals The proposed methodology is based on modifying the flow graph of the FFT algorithm such that it has both real and complex datapaths The imaginary parts of the computations replace the redundant operations in the modified flow graph New butterfly structures are designed to handle the hybrid datapaths The proposed hybrid datapath leads to a general approach which can be extended to all radix- 2n based FFT algorithms Further, architectures with arbitrary level of parallelism can be derived using the folding methodology Novel 2-parallel and 4-parallel architectures are presented for radix- 23 and radix- 24 algorithms The proposed architectures maximize the utilization of hardware components with no redundant computations The proposed radix- 23 and radix- 24 architectures lead to low hardware complexity with respect to adders and delays The N-point 4-parallel radix- 24 architecture requires 2(log16N-1) complex multipliers, 2log2N real adders and N complex delay elements

FFT Architectures for Real-Valued Signals Based on Radix- $2^{3}$ and Radix- $2^{4}$ Algorithms

Turbo decoders may have large decoding latency and low throughput due to iterative decoding. One way to increase the throughput and reduce the latency of turbo decoders is to use high speed decoding schemes. In particular, area-efficient parallel decoding schemes may be used to overcome the decoding latency and throughput associated with turbo decoders. In addition, hybrid parallel decoding schemes may be used in high-level parallelism implementations. Moreover, the area-efficient parallel decoding schemes introduce little or no performance degradation.

Area efficient parallel turbo decoding

This paper presents novel approaches for pipelining of parallel nested multiplexer loops and decision feedback equalizers (DFEs) based on look-ahead techniques. Look-ahead techniques can be applied to pipeline a nested multiplexer loop in many possible ways. It is shown that not all the look-ahead approaches necessarily result in improved performance. A novel look-ahead approach is identified, which can guarantee improvement in performance either in the form of pipelining or parallelism. The proposed technique is demonstrated and applied to design multiplexer-loop-based DFEs with throughput in the range of 3.125-10 Gb/s.

Design of multigigabit multiplexer-loop-based decision feedback equalizers

Digital signal processing algorithms are repetitive in nature. These algorithms are described by iterative data-flow graphs where nodes represent computations and edges represent communications. For all data-flow graphs, there exists a fundamental lower bound on the iteration period referred to as theiteration bound. Determining the iteration bound for signal processing algorithms described by iterative data-flow graphs is an important problem. In this paper we review two existing algorithms for determination of the iteration bound. Then we propose another novel method based on theminimum cycle mean algorithm to determine the iteration bound with a lower polynomial time complexity than the two existing techniques. It is convenient to represent many multi-rate signal processing algorithms by multi-rate data-flow graphs. The iteration bound of a multi-rate data-flow graph (MRDFG) can be determined by considering the single-rate data-flow graph (SRDFG) equivalent of the MRDFG. However, the equivalent single-rate data-flow graph contains many redundant nodes and edges. The iteration bound of the MRDFG can be determined faster if these redundancies in the equivalent SRDFG are first removed. A previous approach has considered elimination of edge redundancy. In this paper we present an approach to eliminatenode redundancy in the MRDFG. We combine elimination of node and edge redundancies to propose a novel algorithm for faster determination of the iteration bound of the MRDFG.

Determining the minimum iteration period of an algorithm

This paper presents a new algorithm for the implementation of discrete cosine transform (DCT), based on the idea of reformulating prime N-length DCT into two cyclic convolutions with exactly the same structure, which are implemented with a proposed fast cyclic convolution-based systolic array structure. The proposed algorithm can save (N-1)/2 multiplications and 2Nregisters, at the cost of only (N-1)/2 additions of those used in previous designs. The I/O is kept low because of the simple control complexity of the algorithm. Furthermore, this new algorithm preserves all the other benefits of very large-scale integration algorithms based on circular correlation or cyclic convolution, such as regular and simple structure.

Keshab K. Parhi

Papers

FFT Architectures for Real-Valued Signals Based on Radix- $2^{3}$ and Radix- $2^{4}$ Algorithms

Area efficient parallel turbo decoding

Design of multigigabit multiplexer-loop-based decision feedback equalizers

Determining the minimum iteration period of an algorithm

A novel systolic array structure for DCT