order within each subset. This side effect is at best innocuous, at worst downrightinconvenient. When thearray is verylong,so thatmaking ascratch copyofit istaxingon memory, or when the computational burden of the selection is a negligible partof a larger calculation, one turns to selection algorith[r]
selection methods by a factor of about 10. We give routines of both types, below.The most common use of selection is in the statistical characterization of a setof data. One often wants to know the median element in an array, or the top andbottom quartile elements. When N is odd, the median is the k[r]
12.4 FFT in Two or More Dimensions521Sample page from NUMERICAL RECIPES IN C: THE ART OF SCIENTIFIC COMPUTING (ISBN 0-521-43108-5)Copyright (C) 1988-1992 by Cambridge University Press.Programs Copyright (C) 1988-1992 by Numerical Recipes Software. Permission is gr[r]
732Chapter 16. Integration of Ordinary Differential EquationsSample page from NUMERICAL RECIPES IN C: THE ART OF SCIENTIFIC COMPUTING (ISBN 0-521-43108-5)Copyright (C) 1988-1992 by Cambridge University Press.Programs Copyright (C) 1988-1992 by Numerical Recipes So[r]
Sample page from NUMERICAL RECIPES IN C: THE ART OF SCIENTIFIC COMPUTING (ISBN 0-521-43108-5)Copyright (C) 1988-1992 by Cambridge University Press.Programs Copyright (C) 1988-1992 by Numerical Recipes Software. Permission is granted for internet users to make one[r]
12.4 FFT in Two or More Dimensions521Sample page from NUMERICAL RECIPES IN C: THE ART OF SCIENTIFIC COMPUTING (ISBN 0-521-43108-5)Copyright (C) 1988-1992 by Cambridge University Press.Programs Copyright (C) 1988-1992 by Numerical Recipes Software. Permission is gr[r]
#define MASK (IB1+IB2+IB5)int irbit2(unsigned long *iseed)Returns as an integer a random bit, based on the 18 low-significance bits iniseed (which ismodified for the next call).{if (*iseed & IB18) { Change all masked bits, shift, and put 1 into bit 1.*iseed=((*iseed ^ MASK) << 1)[r]
= z0+ hf(x, z0)zm+1= zm−1+2hf(x + mh, zm) for m =1,2,...,n−1y(x+H)≈yn≡12[zn+zn−1+hf(x + H, zn)](16.3.2)16.3 Modified Midpoint Method723Sample page from NUMERICAL RECIPES IN C: THE ART OF SCIENTIFIC COMPUTING (ISBN 0-521-43108-5)Copyright (C) 1988-1992 by Cambridge University Pres[r]
36Chapter 2. Solution of Linear Algebraic EquationsSample page from NUMERICAL RECIPES IN C: THE ART OF SCIENTIFIC COMPUTING (ISBN 0-521-43108-5)Copyright (C) 1988-1992 by Cambridge University Press.Programs Copyright (C) 1988-1992 by Numerical Recipes Software. Pe[r]
give additional practical hints.)Figure 14.8.2 shows the result of smoothing the same noisy “data” with broaderSavitzky-Golay filters of 3 different orders. Here we have nL= nR=32(65 point filter)and M =2,4,6. One sees that, when the bumps are too narrow with respect to the filtersize, then even the Sa[r]
198Chapter 5. Evaluation of FunctionsSample page from NUMERICAL RECIPES IN C: THE ART OF SCIENTIFIC COMPUTING (ISBN 0-521-43108-5)Copyright (C) 1988-1992 by Cambridge University Press.Programs Copyright (C) 1988-1992 by Numerical Recipes Software. Permission is gr[r]
894Chapter 20. Less-Numerical AlgorithmsSample page from NUMERICAL RECIPES IN C: THE ART OF SCIENTIFIC COMPUTING (ISBN 0-521-43108-5)Copyright (C) 1988-1992 by Cambridge University Press.Programs Copyright (C) 1988-1992 by Numerical Recipes Software. Permission is[r]
Sample page from NUMERICAL RECIPES IN C: THE ART OF SCIENTIFIC COMPUTING (ISBN 0-521-43108-5)Copyright (C) 1988-1992 by Cambridge University Press.Programs Copyright (C) 1988-1992 by Numerical Recipes Software. Permission is granted for internet users to make one[r]
| is sufficiently small. This is usually the case,but by no means guaranteed. Jones[7]gives a list of theorems that can be used tojustify this termination criterion for various kinds of continued fractions.There is atpresent no rigorousanalysis oferrorpropagationinLentz’s algorithm.However, empirical[r]
Section 14.8 introduces the concept of data smoothing, and discusses theparticular case of Savitzky-Golay smoothing filters.This chapter draws mathematically on the material on special functions thatwas presented in Chapter 6, especially §6.1–§6.4. You may wish, at this point,to review those s[r]
Section 14.8 introduces the concept of data smoothing, and discusses theparticular case of Savitzky-Golay smoothing filters.This chapter draws mathematically on the material on special functions thatwas presented in Chapter 6, especially §6.1–§6.4. You may wish, at this point,to review those s[r]
Gamma DistributionThe gamma distribution of integer order a>0is the waiting time to the athevent in a Poisson random process of unit mean. For example, when a =1,itisjustthe exponential distribution of §7.2, the waiting time to the first event.292Chapter 7. Random NumbersSample page from NUMER[r]
do not have to understand this; just use the values of jinit and jrev specified inthe table. (If you insist on knowing, the explanation is that serial data ports sendcharacters least-significant bit first (!), and many protocols shift bits into the CRCregister in exactly the order received.) The table[r]
if (xm < 12.0) { Use direct method.if (xm != oldm) {oldm=xm;g=exp(-xm); If xm is new, compute the exponential.}em = -1;t=1.0;do { Instead of adding exponential deviates it is equiv-alent to multiply uniform deviates. We neveractually have to take the log, merely com-pare to the pre-computed e[r]
Sample page from NUMERICAL RECIPES IN C: THE ART OF SCIENTIFIC COMPUTING (ISBN 0-521-43108-5)Copyright (C) 1988-1992 by Cambridge University Press.Programs Copyright (C) 1988-1992 by Numerical Recipes Software. Permission is granted for internet users to make one[r]