Harley Myler Myler
Lamar University, Electrical Engineering, Faculty Member
- I have over 40 years in higher education, written books, papers, have patents and saw hundreds of students out into the world with engineering degrees.edit
undamentals of Engineering Programming with C and Fortran is a beginner's guide to problem solving with computers that shows how to quickly prototype a program for a particular engineering application. The book's side-by- side coverage of... more
undamentals of Engineering Programming with C and Fortran is a beginner's guide to problem solving with computers that shows how to quickly prototype a program for a particular engineering application. The book's side-by- side coverage of C and Fortran is unique. Myler emphasizes the importance of developing programming skills in C while carefully presenting the importance of maintaining a good reading knowledge of Fortran. Beginning with a brief description of computer architecture, he then covers the fundamentals of computer programming for problem solving. He also devotes separate chapters to data types and operators, control flow, type conversion, arrays, and file operations. The final chapter contains case studies that illustrate particular elements of modeling and visualization. Also included are a number of appendices covering C and Fortran language summaries and other useful topics. This concise and accessible book can be used as a text for introductory-level undergraduate courses on engineering programming or as a self-study guide for practicing engineers.
Focusing on algorithm programming in C, this practical guide provides clear, concise treatment of the entire spectrum of image processing techniques. Without getting bogged down in complex mathematics, the book covers all aspects of... more
Focusing on algorithm programming in C, this practical guide provides clear, concise treatment of the entire spectrum of image processing techniques. Without getting bogged down in complex mathematics, the book covers all aspects of imaging from basic characterization and modelling through grayscale and spatial manipulation techniques; powerful convolution, spatial frequency, and adaptive filtering methods; and each algorithm group discussed includes C program code to illustrate how the process is programmed.
Machine vision has come of age as an established, respected field of research and application with a strong theoretical foundation. The term 'machine vision' has various definitions, depending on one's field, such as computer vision,... more
Machine vision has come of age as an established, respected field of research and application with a strong theoretical foundation. The term 'machine vision' has various definitions, depending on one's field, such as computer vision, image understanding, scene analysis, or robotics. In this Tutorial Text, machine vision specifically refers to the study and implementation of systems that allow machines to recognize objects from acquired image data and perform useful tasks from that recognition. This book is intended to help readers understand and construct machine vision systems that perform useful tasks, based on the current state of the art. It covers fundamentals drawn from image processing and computer graphics to the methods of applied machine vision techniques. The text is useful as a short course supplement, as a self-study guide, or as a primary or supplementary text in an advanced undergraduate or graduate course.
This handy desktop reference gathers together into one easy-to-use volume the most popular image processing algorithms. Designed to be used at the computer terminal, it features an illustrated, annotated dictionary format — with clear,... more
This handy desktop reference gathers together into one easy-to-use volume the most popular image processing algorithms. Designed to be used at the computer terminal, it features an illustrated, annotated dictionary format — with clear, concise definitions, examples, and C program code. Covers algorithms for adaptive filters, coding and compression, color image processing, histogram operations, image fundamentals, mensuration, morphological filters, nonlinear filters, segmentation, spatial filters, spatial frequency filters, storage formats, and transforms. Includes graphic oriented techniques such as warping, morphing, zooming, and dithering. Provides algorithms for image noise generation.
The development of expert systems and other knowledge-based systems is frequently slowed by the arduous task of knowledge acquisition. For a particular domain, the required knowledge can be extensive, and its extraction from the... more
The development of expert systems and other knowledge-based systems is frequently slowed by the arduous task of knowledge acquisition. For a particular domain, the required knowledge can be extensive, and its extraction from the appropriate source can be astonishingly time consuming. For model-based diagnostic systems, one proposed partial solution to this knowledge acquisition bottleneck is automated knowledge extraction from computer-aided design (CAD) databases.
To build a knowledge base (model) for a model-based diagnostic system, both system structure and component function need to be described. The automated knowledge generation (AKG) system extracts descriptive information about the components of a system as well as their interconnectivity data from CAD databases. Instead of simply performing a direct translation of the CAD data, the modules that compose the AKG system cooperatively correct any inconsistencies in the CAD representations and supply the function information. This information is not found in CAD but is vital for the effective modeling of the systems to be diagnosed and their individual components. The AKG goal to automatically build a functional knowledge base for a model-based diagnostic system with minimal human intervention.
To build a knowledge base (model) for a model-based diagnostic system, both system structure and component function need to be described. The automated knowledge generation (AKG) system extracts descriptive information about the components of a system as well as their interconnectivity data from CAD databases. Instead of simply performing a direct translation of the CAD data, the modules that compose the AKG system cooperatively correct any inconsistencies in the CAD representations and supply the function information. This information is not found in CAD but is vital for the effective modeling of the systems to be diagnosed and their individual components. The AKG goal to automatically build a functional knowledge base for a model-based diagnostic system with minimal human intervention.
