最新的支持向量机工具箱，有了它会很方便 1. Find time to write a proper list of things to do! 2. Documentation. 3. Support Vector Regression. 4. Automated model selection. REFERENCES ========== [1] V.N. Vapnik, "The Nature of Statistical Learning Theory", Springer-Verlag, New York, ISBN 0-387-94559-8, ...
Software Testing, Second Edition provides practical insight into the world of software testing and quality assurance. Learn how to find problems in any computer program, how to plan an effective test approach and how to tell when software is ready for release. Updated from the previous edition in 20 ...
A Java virtual machine instruction consists of an opcode specifying the operation to be performed, followed by zero or more operands embodying values to be operated upon. This chapter gives details about the format of each Java virtual machine instruction and the operation it performs.
A Java virtual machine instruction consists of an opcode specifying the operation to be performed, followed by zero or more operands embodying values to be operated upon. This chapter gives details about the format of each Java virtual machine instruction and the operation it performs.
A Java virtual machine instruction consists of an opcode specifying the operation to be performed, followed by zero or more operands embodying values to be operated upon. This chapter gives details about the format of each Java virtual machine instruction and the operation it performs.
A Java virtual machine instruction consists of an opcode specifying the operation to be performed, followed by zero or more operands embodying values to be operated upon. This chapter gives details about the format of each Java virtual machine instruction and the operation it performs.
MFC Black Book
Introduction:
Are you an MFC programmer? Good. There are two types of MFC programmers. What kind are you? The first kind are the good programmers who write programs that conform to the way MFC wants you to do things. The second bunch are wild-eyed anarchists who insist on getting thin ...
Routine mampres: To obtain amplitude response from h(exp(jw)).
input parameters:
h :n dimensioned complex array. the frequency response is stored
in h(0) to h(n-1).
n :the dimension of h and amp.
fs :sampling frequency (Hz).
iamp:If iamp=0: The Amplitude Res. amp(k)=abs(h(k))
If iamp=1: The ...
Routine mar1psd: To compute the power spectum by AR-model parameters.
Input parameters:
ip : AR model order (integer)
ep : White noise variance of model input (real)
ts : Sample interval in seconds (real)
a : Complex array of AR parameters a(0) to a(ip)
Output parameters:
psdr : Real array of ...
