Physical Sciences and Mathematics Commons^™

Performance Of Combined Diversity Reception And Convolutional Coding For Qdpsk Land Mobile Radio, Huafei Zhou, Robert H. Deng, T. T. Tjhung

Research Collection School Of Computing and Information Systems

Diversity reception and error correction coding are powerful techniques to combat multipath fading encountered in mobile radio communications. In order to improve the transmission performance of the ?/4-shift QDPSK signal in mobile radio channels, the authors propose a new scheme of combined coding and diversity reception, i.e., combination of diversity reception employing code combining (CC) and convolutional coding employing error-and erasure correction Viterbi decoding. They also consider another combination scheme, i.e., combination of diversity reception employing postdetection maximal ratio combining (MRC) and convolutional coding employing hard decision Viterbi decoding. They theoretically analyze the performance of the schemes taking into account …

Optimum Symbol-By-Symbol Detection Of Uncoded Digital Data Over The Gaussian Channel With Unknown Carrier Phase, Pooi Yuen Kam, Seng Siew Ng, Tock Soon Ng

Research Collection School Of Computing and Information Systems

A theory of optimum receiver design for symbol-by-symbol detection of an uncoded digital data sequence received over the Gaussian channel with unknown carrier phase is presented. Linear suppressed-carrier modulation is assumed. The work here aims at laying a conceptual foundation for optimum symbol-by-symbol detection, and rectifies existing approaches to the problem. The optimum receiver structure is obtained explicitly for an arbitrary carrier phase model, but its computational requirements are too heavy in general for any practical implementation. In one important special case, namely, the case in which the carrier phase can be treated as a constant over some K+1 symbol …

A New Parallel Technique For The Solution Of Sparse Nonlinear Equations, Maria Cereijo Martinez

FIU Electronic Theses and Dissertations

Solving nonlinear systems of equations is a central problem in numerical analysis, with enormous significance for science and engineering. A special case, sparse systems of equations, occurs frequently in various applications. Sparsity occurs in the analysis of many types of complex systems because of the local nature of the dependence or connectivity among system components.

One such system which may be modeled by a nonlinear sparse set of equations is the power system load flow analysis. This is a mathematical study performed by electrical utilities to monitor the electrical power system. The data from system components are used to create …

A Detailed Simulation Model Of The Hp 97560 Disk Drive, David Kotz, Song Bac Toh, Sriram Radhakrishnan

Computer Science Technical Reports

We implemented a detailed model of the HP 97560 disk drive, to replicate a model devised by Ruemmler and Wilkes (both of Hewlett-Packard, HP). Our model simulates one or more disk drives attached to one or more SCSI buses. The design is broken into three components: a test driver, the disk model itself, and the discrete-event simulation support. Thus, the disk model can be easily extracted and used in other simulation environments. We validated our model using traces obtained from HP, using the same "demerit" measure as Ruemmler and Wilkes. We obtained a demerit percentage of 3.9%, indicating that our …

A 2-3/4-Approximation Algorithm For The Shortest Superstring Problem, Chris Armen, Clifford Stein

Computer Science Technical Reports

Given a collection of strings S={s_1,...,s_n} over an alphabet Sigma, a superstring alpha of S is a string containing each s_i as a substring, that is, for each i, 1<=i<=n, alpha contains a block of |s_i| consecutive characters that match s_i exactly. The shortest superstring problem is the problem of finding a superstring alpha of minimum length. The shortest superstring problem has applications in both computational biology and data compression. The problem is NP-hard [GallantMS80]; in fact, it was recently shown to be MAX SNP-hard [BlumJLTY91]. Given the importance of the applications, several heuristics and approximation algorithms have been proposed. Constant factor approximation algorithms have been given in [BlumJLTY91] (factor of 3), [TengY93] (factor of 2-8/9), [CzumajGPR94] (factor of 2-5/6) and [KosarajuPS94] (factor of 2-50/63). Informally, the key to any algorithm for the shortest superstring problem is to identify sets of strings with large amounts of similarity, or overlap. While the previous algorithms and their analyses have grown increasingly sophisticated, they reveal remarkably little about the structure of strings with large amounts of overlap. In this sense, they are solving a more general problem than the one at hand. In this paper, we study the structure of strings with large amounts of overlap and use our understanding to give an algorithm that finds a superstring whose length is no more than 2-3/4 times that of the optimal superstring. We prove several interesting properties about short periodic strings, allowing us to answer questions of the following form: given a string with some periodic structure, characterize all the possible periodic strings that can have a large amount of overlap with the first string.

Efficiency And Stability Issues In The Numerical Computation Of Fourier Transforms And Convolutions On The 2-Sphere, D M. Healy Jr, S S. B. Moore, D Rockmore

Computer Science Technical Reports

Earlier work by Driscoll and Healy has produced an efficient algorithm for computing the Fourier transform of band-limited functions on the sphere. In this paper we present a greatly improved inverse transform, and consequent improved convolution algorithm for such functions. We also discuss implementational considerations and give heuristics for allowing reliable floating point implementations of a slightly modified algorithm at little cost in either theoretical or actual performance. This discussion is supplemented with numerical experiments from our implementation in C on a DecStation 5000. These results give strong indications that the algorithm is both reliable and efficient for a large …

Bergman Spaces On Disconnected Domains, Alexandru Aleman, Stefan Richter, William T. Ross

Department of Math & Statistics Technical Report Series

For a bounded region G ⊂ ℂ and a compact set K ⊂G , with area measure zero, we will characterize the invariant subspaces M (under ƒ → z ƒ) of the Bergman space L^p_a(G\K), 1 ≤ p < ∞, which contain L<sup>p_a(G) and with dim(M/(z-⋋)M) = 1 for all ⋋ ∈ G\K. When G\K is connected, we will see that dim(M/(z-⋋)M) = 1 for all ⋋ ∈ G\K and this in this case we will have a complete …

An Adaptable Constrained Locking Protocol For High Data Contention Environments, Shalab Goel, Bharat Bhargava

Department of Computer Science Technical Reports

No abstract provided.

Stability Analysis Of Quota Allocation Access Protocols In Ring Networks With Spatial Reuse, Leonidas Georgiadis, Wojciech Szpankowski, Leondros Tassiulas

Department of Computer Science Technical Reports

No abstract provided.

Metrics To Evaluate Academic Departments, John R. Rice

Department of Computer Science Technical Reports

No abstract provided.

Modeling Scattered Function Data On Curved Surfaces, Chandrajit L. Bajaj, Guoliang Xu

Department of Computer Science Technical Reports

No abstract provided.

A Study Of Computer Hardware And Software Usage In The Wichita, Kansas Area Business Community, Cheryl L. Rogers

Electronic Theses & Dissertations

For the purpose of informationally equipping educational institutions to prepare students for a future in the business world, this study was conducted with the intent of identifying and analyzing the current computer hardware and software used for word processing, spreadsheet, database, and desktop publishing tasks in Wichita, Kansas, selected area businesses and industries. In addition, this study was designed to determine the factors the business community respondents considered in choosing their computer hardware and software. Finally, the study was intended to ascertain the length of time since computer hardware and software changes had been made within the responding companies and …

Automated Manpower Rostering: Techniques And Experience, C. M. Khoong, Hoong Chuin Lau, L. W. Chew

Research Collection School Of Computing and Information Systems

We present ROMAN, a comprehensive, generic manpower rostering toolkit that successfully handles a wide spectrum of work policies found in service organizations. We review the use of various techniques and methodologies in the toolkit that contribute to its robustness and efficiency, and relate experience gained in addressing manpower rostering problems in industry.

On A Learnability Question Associated To Neural Networks With Continuous Activations, Bhaskar Dasgupta, Hava Siegelmann, Eduardo Sontag

Hava Siegelmann

This paper deals with learnability of concept classes defined by neural networks, showing the hardness of PAC-learning (in the complexity, not merely information-theoretic sense) for networks with a particular class of activation. The obstruction lies not with the VC dimension, which is known to grow slowly; instead, the result follows the fact that the loading problem is NP-complete. (The complexity scales badly with input dimension; the loading problem is polynomial-time if the input dimension is constant). Similar and well-known theorems had already been proved by Megiddo and by Blum and Rivest, for binary-threshold networks. It turns out the general problem …

Parallel Computer Needs At Dartmouth College, David Kotz, Fillia Makedon, Matt Bishop, Scot Drysdale, Don Johnson, Takis Metaxas

Computer Science Technical Reports

To determine the need for a parallel computer on campus, a committee of the Graduate Program in Computer Science surveyed selected Dartmouth College faculty and students in December, 1991, and January, 1992. We hope that the information in this report can be used by many groups on campus, including the Computer Science graduate program and DAGS summer institute, Kiewit's NH Supercomputer Initiative, and by numerous researchers hoping to collaborate with people in other disciplines.

We found significant interest in parallel supercomputing on campus. An on-campus parallel supercomputing facility would not only support numerous courses and research projects, but would provide …

Analysis Of Myoelectrical Signals For Building A Dextrous Hand, Christopher T. Creel, Kishan Mehrotra, Chilukuri K. Mohan, Sanjay Ranka

Electrical Engineering and Computer Science - Technical Reports

We analyze techniques for myoelectrical signals classification for the purpose of designing a multifunctional prosthetic device for human amputees. The main advantage of our system over existing models is that it is more robust, easier to work with, more general, and efficient enough to run in real time. We achieve this with the help of "Supervised Growing Cell Structures." an artificial neural network model designed by Fritzke [10]. The current paper focuses on the flexion of the index, middle and ring fingers, as these are the most difficult movements to tackle.

Bmmc Permutations On A Decmpp 12000/Sx 2000, Kristin Bruhl

Dartmouth College Undergraduate Theses

Increasingly, modern computing problems, including many scientific and business applications, require huge amounts of data to be examined, modified, and stored. Parallel computers can be used to decrease the time needed to operate on such large data sets, by allowing computations to be performed on many pieces of data at once. For example, on the DECmpp machine used in our research, there are 2048 processors in the parallel processor array. The DECmpp can read data into each of these processors, perform a computation in parallel on all of it, and write the data out again, theoretically decreasing the execution time …

Scalar Field Modeling & Visualization On The Intel Delta, Chandrajit Bajaj, Kwun-Nan Lin

Department of Computer Science Technical Reports

No abstract provided.

Processing Pde Interface Conditions, John R. Rice

Department of Computer Science Technical Reports

No abstract provided.

Curvature Continuous Spline Surfaces Over Irregular Meshes, Jörg Peters

Department of Computer Science Technical Reports

No abstract provided.

Eppod: A Problem Solving Environment For Parallel Electronic Prototyping Of Physical Object Design, Poting Wu, Elias N. Houstis, John R. Rice

Department of Computer Science Technical Reports

No abstract provided.

An Analysis Of The Paging Activity Of Parallel Programs, Kuei Yu Wang, Dan C. Marinescu

Department of Computer Science Technical Reports

No abstract provided.

A Conceptual Model For Multimedia Database Systems, Shunge Li, Xiangning Liu, Bharat Bhargava

Department of Computer Science Technical Reports

No abstract provided.

Converting A Rational Surface To A Standard Rational Bernstein-Bezier Surface, Chandrajit Bajaj, Guoliang Xu

Department of Computer Science Technical Reports

No abstract provided.

Sparse Smooth Connection Between Bezier/Bspline Curves, Chandrajit Bajaj, Guoliang Xu

Department of Computer Science Technical Reports

No abstract provided.

Identification Of Cutting Force In End Milling Operations Using Recurrent Neural Networks, Q. Xu, K. Krishnamurthy, Bruce M. Mcmillin, Wen Feng Lu

Mechanical and Aerospace Engineering Faculty Research & Creative Works

The problem of identifying the cutting force in end milling operations is considered in this study. Recurrent neural networks are used here and are trained using a recursive least squares training algorithm. Training results for data obtained from a SAJO 3-axis vertical milling machine for steady slot cuts are presented. The results show that a recurrent neural network can learn the functional relationship between the feed rate and steady-state average resultant cutting force very well. Furthermore, results for the Mackey-Glass time series prediction problem are presented to illustrate the faster learning capability of the neural network scheme presented here

Wright State University College Of Engineering And Computer Science Bits And Pcs Newsletter, Volume 10, Number 6, June 1994, College Of Engineering And Computer Science, Wright State University

BITs and PCs Newsletter

A ten page newsletter created by the Wright State University College of Engineering and Computer Science that addresses the current affairs of the college.

A Recursive Least Squares Training Algorithm For Multilayer Recurrent Neural Networks, Q. Xu, K. Krishnamurthy, Bruce M. Mcmillin, Wen Feng Lu

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Recurrent neural networks have the potential to perform significantly better than the commonly used feedforward neural networks due to their dynamical nature. However, they have received less attention because training algorithms/architectures have not been well developed. In this study, a recursive least squares algorithm to train recurrent neural networks with an arbitrary number of hidden layers is developed. The training algorithm is developed as an extension of the standard recursive estimation problem. Simulated results obtained for identification of the dynamics of a nonlinear dynamical system show promising results.

Human Creativity Through Computer Gaming, Christine Mcgavran

Dartmouth College Undergraduate Theses

No abstract provided.

Feature And Model Selection In Feedforward Neural Networks, Jean M. Steppe

Theses and Dissertations

This research advances feature and model selection for feedforward neural networks. Feature selection involves determining a good feature subset given a set of candidate features. Model selection involves determining an appropriate architecture number of middle nodes for the neural network. Specific advances are made in neural network feature saliency metrics used for evaluating or ranking features, statistical identification of irrelevant noisy features, and statistical investigation of reduced neural network architectures and reduced feature subsets. New feature saliency metrics are presented which provide a more succinct quantitative measure of a features importance than other similar metrics. A catalogue of feature saliency …