This code detects memory leaks in embedded VC++ almost the same way crtdbg does in VC++. At the end of program execution it will display in the debug window if there were any memory leaks and how the memory looks so you can identify where your memory leak occurred. It will display in the debug window a message saying no memory leaks detected if there are no memory leaks. Similar to what crtdbg.h does in VC++. The code detects memory leaks generated with calls to new and delete operators in C++. The code doesn t detect memory leaks generated with C functions: malloc, calloc, free, but that can be done in the future. Let me know and I will program it.
This class implements the same API as the Java 1.3 java.util.TimerTask.
* Note that a TimerTask can only be scheduled on one Timer at a time, but
* that this implementation does not enforce that constraint.
fastDNAml is an attempt to solve the same problem as DNAML, but to do so
faster and using less memory, so that larger trees and/or more bootstrap
replicates become tractable. Much of fastDNAml is merely a recoding of the
PHYLIP 3.3 DNAML program from PASCAL to C.
The same two-stage decoder as above. However, when transforming the symbols prior to Viterbi decoding, the amplitude information is ignored and only the phase of the received symbol is employed in the metric computation stage.
The Viterbi algorithm is the same as the binary case with one main difference: The survivor sequences include the uncoded bits, which are decided at each trellis stage when selecting one of two parallel branches with the largest correlation metric.
Presently, only 8-PSK modulation is considered. Extensions to higher-order modulations can be implemented following a similar procedure.
Computes the hafnian of a nonnegative integer matrix. Notes: Copy hafnian.c to main.c, in the same directory as Rothberg s code (see above). You can download the .tar directory with the code weighted-match.tar here. Then "make" the codes (this codes are in C, not C++). The program is then run by the command "wmatch".
SOUNDSC(Y,...) is the same as SOUND(Y,...) except the data is
scaled so that the sound is played as loud as possible without
clipping. The mean of the data is removed.
