elaine ayota
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| import numpy as np | |
| import scikits.audiolab | |
| import scipy | |
| f = 440 | |
| fs = 11025 #22050 | |
| T = 0.1 | |
| x = scipy.cos((2*scipy.pi*f/fs)*scipy.arange(fs*T)) | |
| for y in range(0,1000): |
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| 2. | |
| ```{r} | |
| #make matrices | |
| set.seed(693) | |
| A <- matrix(ceiling(runif(4, min=100, max=999)), nrow=2, ncol=2) | |
| B <- matrix(ceiling(runif(4, min=-9, max=9)), nrow=2, ncol=2) | |
| C <- matrix(ceiling(-runif(4, min=100, max=999)), nrow=2, ncol=2) | |
| Z <- matrix(0, nrow=2, ncol=2) | |
| M <- rbind(cbind(Z,Z,A), cbind(Z,B,Z), cbind(C,Z,Z)) |
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| 2. | |
| ```{r} | |
| #make matrices | |
| set.seed(693) | |
| A <- matrix(ceiling(runif(4, min=100, max=999)), nrow=2, ncol=2) | |
| B <- matrix(ceiling(runif(4, min=-9, max=9)), nrow=2, ncol=2) | |
| C <- matrix(ceiling(-runif(4, min=100, max=999)), nrow=2, ncol=2) | |
| Z <- matrix(0, nrow=2, ncol=2) | |
| M <- rbind(cbind(Z,Z,A), cbind(Z,B,Z), cbind(C,Z,Z)) |
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| 2. | |
| ```{r} | |
| #make matrices | |
| set.seed(693) | |
| A <- matrix(ceiling(runif(4, min=100, max=999)), nrow=2, ncol=2) | |
| B <- matrix(ceiling(runif(4, min=-9, max=9)), nrow=2, ncol=2) | |
| C <- matrix(ceiling(-runif(4, min=100, max=999)), nrow=2, ncol=2) | |
| Z <- matrix(0, nrow=2, ncol=2) | |
| M <- rbind(cbind(Z,Z,A), cbind(Z,B,Z), cbind(C,Z,Z)) |
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| power2 <- function(B1 = B1, B2 = B2, v1.old = u1, v2.old = u2, p = .15) { | |
| N <- length(v1.old) | |
| B1.p <- matrix(0, ncol=5242, nrow=5242) | |
| B1.p <- sapply(1:5242, function(x) (1-p)/sum(B1[x,]) * B1[x,]) | |
| B2.p <- (p/N) * B2 | |
| v1.new <- B1.p %*% v1.old + B2.p %*% v1.old | |
| v1.new <- v1.new / norm(v1.new) | |
| v2.new <- B1.p %*% v2.old + B2.p %*% v2.old |
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| power <- function(B1 = B1, B2 = B2, v.old = v, tol = 10^-10, p = .15) { | |
| N <- length(v) | |
| B.p <- matrix(0, ncol=5242, nrow=5242) | |
| B.p <- sapply(1:5242, function(x) (1-p)/sum(B1[x,]) * B1[x,]) | |
| v.old <- v | |
| v.new <- B.p %*% v.old + (p/N) * B2 %*% v.old | |
| v.new <- v.new / norm(v.new) | |
| i <- 0 |
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| Elaine Ayo | |
| Math 504 / Homework 10 | |
| March 29, 2015 | |
| ```{r echo=FALSE, message=FALSE} | |
| library(MASS) | |
| library(Matrix) | |
| library(ggplot2) |
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| data <- read.table("~/Dropbox/numericalmethods/nonlinear.txt", header=TRUE, quote="\"") | |
| #param order: d, r | |
| fxn.4 <- list( | |
| f.x = function(params, data) return( sum((data$y - params[1]*exp(-params[2] * data$x) )^2) ), | |
| grad = function(params, data, f.x, h) { | |
| d.d <- (f.x(params = c(params[1] + h, params[2]), data) - f.x(params, data)) / h | |
| d.r <- (f.x(params = c(params[1], params[2] + h), data) - f.x(params, data)) / h | |
| return(c(d.d,d.r)) | |
| }, |
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