Visual C++ has been one of most effective tool for the large industrial applications. This book is the best resource I have ever found on Industrial Applications of Visual C++.
In C Algorithms for Real-Time DSP, author Paul M. Embree presents a complete guide to digital signal processing techniques in the C programming language. This book is structured in such a way that it will be most useful to the engineer who is familiar with DSP and the C language, but who is not necessarily an expert in both. All of the example programs in this book have been tested using standard C compilers in the UNIX and MS-DOS programming environments. In addition, the examples have been compiled using the real-time programing tools of specific real-time embedded DSP microprocessors (Analog Devices ADSP-21020 and ADSP-21062 Texas Instruments TMS320C30 and TMS320C40 and AT&T DSP32C) and then tested with real-time hardware using real-world signals.
C in A Nutshell
Learning a language--any language--involves a process wherein you learn to rely less and less on instruction and more increasingly on the aspects of the language you ve mastered. Whether you re learning French, Java, or C, at some point you ll set aside the tutorial and attempt to converse on your own. It s not necessary to know every subtle facet of French in order to speak it well, especially if there s a good dictionary available. Likewise, C programmers don t need to memorize every detail of C in order to write good programs. What they need instead is a reliable, comprehensive reference that they can keep nearby. C in a Nutshell is that reference.
The C++ Cookbook will make your path to mastery much shorter. This practical, problem-solving guide is ideal if you re an engineer, programmer, or researcher writing an application for one of the legions of platforms on which C++ runs. The algorithms provided in C++ Cookbook will jump-start your development by giving you some basic building blocks that you don t have to develop on your own.
Electronics Design Checklist
C) 2003 Hank Wallace
This is a checklist for electronics designers. The idea is for engineers and technicians to
share experiences and create a detailed checklist, which the individual designer can pare down to meet his or her specific needs. There are many details that go into the making
of a first-run design success, and this checklist helps prevent Murphy s gremlins from
marring an otherwise healthy design.
A user-space device driver can do many of the things that kernel drivers can t, such as perform a long-running computation, block while waiting for an event, or read files from the file system. Unlike kernel drivers, a user-space device driver can use other device drivers--that is, access the network, talk to a serial port, get interactive input from the user, pop up GUI windows, or read from disks. User-space drivers implemented using FUSD can be much easier to debug it is impossible for them to crash the machine, are easily traceable using tools such as gdb, and can be killed and restarted without rebooting even if they become corrupted. FUSD drivers don t have to be in C--Perl, Python, or any other language that knows how to read from and write to a file descriptor can work with FUSD. User-space drivers can be swapped out, whereas kernel drivers lock physical memory.
*** HyperString v6.0 ***
(c)1996-2000 EFD Systems, All rights reserved
efd@mindspring.com
*** THIS IS NOT PUBLIC DOMAIN SOFTWARE ***
See below for license agreement, disclaimer, installation and use.
Introduction ---------------------------------------------------------
Welcome to HyperString!
One of the most significant new features with Delphi32 is long dynamic
strings. However, the built-in functions don t really exploit the full
potential of these new strings. HyperString provides over 400 fast,
efficient string management routines to help you realize the full power
of this highly versatile new data type.
P3.20. Consider an analog signal xa (t) = sin (2πt), 0 ≤t≤ 1. It is sampled at Ts = 0.01, 0.05,
and 0.1 sec intervals to obtain x(n).
b) Reconstruct the analog signal ya (t) from the samples x(n) using the sinc interpolation
(use ∆ t = 0.001) and determine the frequency in ya (t) from your plot. (Ignore the end
effects.)
C) Reconstruct the analog signal ya (t) from the samples x (n) using the cubic spline
interpolation and determine the frequency in ya (t) from your plot. (Ignore the end effects.)
