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

Linear feedback shift register (LFSR) is an important part of the cyclic redundancy check (CRC) operations and BCH encoders. This paper presents a novel high speed parallel LFSR architecture based on parallel Infinite Impulse Response (IIR) filter design, pipelining and retiming algorithms. A new formulation is proposed to modify the LFSR into the form of an IIR filter. Then pipelining and retiming algorithms are applied to further reduce the critical path in the parallel architecture. A comparison between the proposed and previous architectures shows that our parallel architecture achieves a critical path same as that of previous designs with a reduced hardware cost.

Efficient parallel VLSI architecture for linear feedback shift registers

This paper proposes a novel parallel approach for pipelining of nested multiplexer loops to design high speed decision feedback equalizers (DFEs) based on look-ahead techniques. It is well known that the DFE is an efficient scheme to suppress intersymbol interference (ISI) in various communication and magnetic recording systems. However, the feedback loop within a DFE limits an upper bound of the achievable high speed in hardware implementation. A straightforward parallel implementation requires more hardware complexity. The novel proposed technique offers significant reduction of hardware complexity of 56% and 80% over the conventional parallel six-tap DFE architectures for 10 Gbps and 20 Gbps throughput, respectively.

Low Complexity Design of High Speed Parallel Decision Feedback Equalizers

Successive cancellation list (SCL) decoding algorithm is a powerful method that can help polar codes achieve excellent error-correcting performance. However, the current SCL algorithm and decoders are based on likelihood or log-likelihood forms, which render high hardware complexity. In this paper, we propose a log-likelihood-ratio (LLR)-based SCL (LLR-SCL) decoding algorithm, which only needs half the computation and storage complexity than the conventional one. Then, based on the proposed algorithm, we develop low-complexity VLSI architectures for LLR-SCL decoders. Analysis results show that the proposed LLR-SCL decoder achieves 50% reduction in hardware and 98% improvement in hardware efficiency.

Successive Cancellation List Polar Decoder using Log-likelihood Ratios

The implementation of video data format using a minimum number of registers is considered. A systematic lifetime analysis of the variables is carried out to determine the latency and the minimum number of registers needed for the converter. The technique of obtaining the minimum number of registers is illustrated using four classes of data format converters: line-by-line to column-by-column, line-by-line to interleaved skewed one-dimensional block format, line-by-line to interleaved two-dimensional block format, and line-by-line to zigzag format. Closed-form expressions for minimum number of registers in these converters are obtained in terms of the number of input and output pixels processed per cycle and the number of input and output bits processed per pixel in a cycle. >

Video data format converters using minimum number of registers

Convolutional Neural Networks (CNN) are widely used in different artificial intelligence (AI) applications. Major part of the computation of a CNN involves 2D convolution. In this paper, we propose novel fast convolution algorithms for both 1D and 2D to remove the redundant multiplication operations in convolution computations at the cost of controlled increase of addition operations. For example, when the 2D processing block size is 3×3, our algorithm has multiplication saving factor as high as 3.24, compared to direct 2D convolution computation scheme. The proposed algorithm can also process input feature maps and generate output feature maps with the same flexible block sizes that are independent of convolution weight kernel size. The memory access efficiency is also largely improved by the proposed method. These structures can be applied to different CNN layers, such as convolution with stride > 1, pooling and deconvolution by exploring flexible feature map processing tile sizes. The proposed algorithm is suitable for both software and hardware implementation.

Keshab K. Parhi

Papers

Efficient parallel VLSI architecture for linear feedback shift registers

Low Complexity Design of High Speed Parallel Decision Feedback Equalizers

Successive Cancellation List Polar Decoder using Log-likelihood Ratios

Video data format converters using minimum number of registers

Fast 2D Convolution Algorithms for Convolutional Neural Networks