Computer recommendations for an automatic approach and landing system for V/STOL aircraft. Volume 1 - Computer recommendations

Evaluation of digital computer for V/STOL aircraft automatic approach and landing syste

MIDAS, prototype Multivariate Interactive Digital Analysis System for large area earth resources surveys. Volume 1: System description

A third-generation, fast, low cost, multispectral recognition system (MIDAS) able to keep pace with the large quantity and high rates of data acquisition from large regions with present and projected sensots is described. The program can process a complete ERTS frame in forty seconds and provide a color map of sixteen constituent categories in a few minutes. A principle objective of the MIDAS program is to provide a system well interfaced with the human operator and thus to obtain large overall reductions in turn-around time and significant gains in throughput. The hardware and software generated in the overall program is described. The system contains a midi-computer to control the various high speed processing elements in the data path, a preprocessor to condition data, and a classifier which implements an all digital prototype multivariate Gaussian maximum likelihood or a Bayesian decision algorithm. Sufficient software was developed to perform signature extraction, control the preprocessor, compute classifier coefficients, control the classifier operation, operate the color display and printer, and diagnose operation

Highly parallel sparse Cholesky factorization

Several fine grained parallel algorithms were developed and compared to compute the Cholesky factorization of a sparse matrix. The experimental implementations are on the Connection Machine, a distributed memory SIMD machine whose programming model conceptually supplies one processor per data element. In contrast to special purpose algorithms in which the matrix structure conforms to the connection structure of the machine, the focus is on matrices with arbitrary sparsity structure. The most promising algorithm is one whose inner loop performs several dense factorizations simultaneously on a 2-D grid of processors. Virtually any massively parallel dense factorization algorithm can be used as the key subroutine. The sparse code attains execution rates comparable to those of the dense subroutine. Although at present architectural limitations prevent the dense factorization from realizing its potential efficiency, it is concluded that a regular data parallel architecture can be used efficiently to solve arbitrarily structured sparse problems. A performance model is also presented and it is used to analyze the algorithms

Exploiting smallest error to calibrate non-linearity in SAR ADCs

This paper presents a statistics-optimised organisation technique to achieve better element matching in Successive Approximation Register (SAR) Analog-to-Digital Converter (ADC) in smart sensor systems. We demonstrate the proposed technique ability to achieve a significant improvement of around 23 dB on Spurious Free Dynamic Range (SFDR) of the ADC than the conventional, testing with a capacitor mismatch σu = 0.2% in a 14 bit SAR ADC system. For the static performance, the max root mean square (rms) value of differential nonlinearity (DNL) reduces from 1.63 to 0.20 LSB and the max rms value of integral nonlinearity (INL) reduces from 2.10 to 0.21 LSB. In addition, it is demonstrated that by applying grouping optimisation and strategy optimisation, the performance boosting on SFDR can be effectively achieved. Such great improvement on the resolution of the ADC only requires an off-line pre-processing digital part

A floating-point/multiple-precision processor for airborne applications

A compact input output (I/O) numerical processor capable of performing floating-point, multiple precision and other arithmetic functions at execution times which are at least 100 times faster than comparable software emulation is described. The I/O device is a microcomputer system containing a 16 bit microprocessor, a numerical coprocessor with eight 80 bit registers running at a 5 MHz clock rate, 18K random access memory (RAM) and 16K electrically programmable read only memory (EPROM). The processor acts as an intelligent slave to the host computer and can be programmed in high order languages such as FORTRAN and PL/M-86

Flying on the wings of genius: a chronicle of modern physics: Book 2

This book is a must read for everyone interested in the future role and direction of science. It begins with the description of the new discoveries made at the turn of the previous century, which have culminated in the scientific knowledge we have today.The book then discusses the fundamental constants of Nature and how they inter-relate and why they may have come to be what they are. This second book compliments and adds a vast new tranche of knowledge to Book I of the series, but is at the same time entirely readable in its own right. As it chronicles the development of modern science it opens a new window on our understanding of science at the most fundamental level of knowledge

An efficient IEEE754 compliant floating point unit using verilog

A floating-point unit (FPU) colloquially is a math coprocessor, which is a part of a computer system specially designed to carry out operations on floating point numbers [1]. Typical operations that are handled by FPU are addition, subtraction, multiplication and division. The aim was to build an efficient FPU that performs basic as well as transcendental functions with reduced complexity of the logic used reduced or at least comparable time bounds as those of x87 family at similar clock speed and reduced the memory requirement as far as possible. The functions performed are handling of Floating Point data, converting data to IEEE754 format, perform any one of the following arithmetic operations like addition, subtraction, multiplication, division and shift operation and transcendental operations like square Root, sine of an angle and cosine of an angle. All the above algorithms have been clocked and evaluated under Spartan 3E Synthesis environment. All the functions are built by possible efficient algorithms with several changes incorporated at our end as far as the scope permitted. Consequently all of the unit functions are unique in certain aspects and given the right environment(in terms of higher memory or say clock speed or data width better than the FPGA Spartan 3E Synthesizing environment) these functions will tend to show comparable efficiency and speed ,and if pipelined then higher throughput