Newconceptdataanalyze
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Новый подход, используя функции матлаб, а не рукописные, позволил улучшить качество счёта и невероятно повысил скорость.
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Concept of c
This document discusses three ways to perform addition of two numbers using only one variable in C and C++ programming.
The first method uses a function that accepts user input for the variable and returns its value. This function is called twice in the main method to perform the addition.
The second method uses scope resolution to access a global variable. It accepts input, performs the addition, and prints the result.
The third method also uses a function but returns the variable value directly to perform the addition in the main method. It accepts input inside the function and returns the variable.
bubble point calculations (MATLAB)
The bubble point is the temperature at which the first drop of a liquid mixture begins to vaporize. This occurs when either the temperature is increased or the pressure is decreased. The document provides an example of calculating the bubble point temperature using MATLAB by defining a nonlinear equation and solving it using a root-finding function (fzero).
Android Refactoring
The document discusses refactoring code to improve its structure and readability without changing its external behavior. It defines refactoring as restructuring software to make it easier to understand and modify. The goals of refactoring are to reduce technical debt by improving code quality. Examples show refactoring an Android app by extracting methods, renaming variables for clarity, and converting the architecture to MVP pattern to separate concerns. Lessons recommend writing unit tests first and using metrics as a guide rather than mandate when refactoring.
Actividad 1 taller de expresiones algoritmicas
The document contains 14 math or logic expressions with variables a, b, c, and d assigned values. Each expression is followed by "R/ta" which likely stands for the result or target answer of evaluating that expression. The expressions include operations like addition, subtraction, multiplication, division, exponents, modulo, Boolean logic, and comparisons using symbols like =, <, >, and, or, not.
Oop lecture1
The document compares a C program that calculates student GPAs in different ways to an equivalent Java program using object-oriented principles. The C program defines a struct and separate functions to calculate the GPA using different methods, while the Java program defines classes to encapsulate the GPA calculation logic and allow code reuse through inheritance. Object-oriented programming aims to maximize code reuse and minimize recoding. To start programming in OOP, a class is defined as a template, with main() as the entry point and javac/java to compile and run Java programs.
Matlab code
This document describes a script that simulates bit error rate (BER) performance for BPSK modulation over a Rayleigh fading channel with a 2 transmitter and 2 receiver (2x2) multiple-input multiple-output (MIMO) system using zero forcing equalization. The script generates transmitted bits, applies BPSK modulation, sends the signals over a Rayleigh fading channel with additive noise, uses zero forcing equalization at the receiver, and compares the estimated and transmitted bits to calculate the simulated BER over a range of signal-to-noise ratio (SNR) values. The simulated results are then plotted along with theoretical BER curves for 1x1 and 2x2 MIMO systems.
Lab manualsahu[et&t]
This document contains 10 experiments on numerical analysis and C programming. Each experiment includes the aim, C code implementation, and sample output for programs that calculate sphere volume and area, sum of digits in a number, triangle property classification, checking for Pythagorean triplets, printing prime numbers within a range, calculating digit sum using a function, reversing an integer using recursion, summing even numbers recursively, sorting an array using bubble sort, and finding the intersection of values in two arrays.
04 - Scala. Type of natural numbers
This document discusses representations of natural numbers in programming languages like Haskell, Scala, and Java. It presents natural numbers as a type with two constructors: Zero and Suc. It also presents an eliminator and computation rules for reducing terms, as well as a uniqueness principle for natural numbers. Examples are given of defining and proving properties of functions over natural numbers using a proof assistant called ProvingGround.
Recommended
Concept of c
This document discusses three ways to perform addition of two numbers using only one variable in C and C++ programming.
The first method uses a function that accepts user input for the variable and returns its value. This function is called twice in the main method to perform the addition.
The second method uses scope resolution to access a global variable. It accepts input, performs the addition, and prints the result.
The third method also uses a function but returns the variable value directly to perform the addition in the main method. It accepts input inside the function and returns the variable.
bubble point calculations (MATLAB)
The bubble point is the temperature at which the first drop of a liquid mixture begins to vaporize. This occurs when either the temperature is increased or the pressure is decreased. The document provides an example of calculating the bubble point temperature using MATLAB by defining a nonlinear equation and solving it using a root-finding function (fzero).
Android Refactoring
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Actividad 1 taller de expresiones algoritmicas
The document contains 14 math or logic expressions with variables a, b, c, and d assigned values. Each expression is followed by "R/ta" which likely stands for the result or target answer of evaluating that expression. The expressions include operations like addition, subtraction, multiplication, division, exponents, modulo, Boolean logic, and comparisons using symbols like =, <, >, and, or, not.
Oop lecture1
The document compares a C program that calculates student GPAs in different ways to an equivalent Java program using object-oriented principles. The C program defines a struct and separate functions to calculate the GPA using different methods, while the Java program defines classes to encapsulate the GPA calculation logic and allow code reuse through inheritance. Object-oriented programming aims to maximize code reuse and minimize recoding. To start programming in OOP, a class is defined as a template, with main() as the entry point and javac/java to compile and run Java programs.
Matlab code
This document describes a script that simulates bit error rate (BER) performance for BPSK modulation over a Rayleigh fading channel with a 2 transmitter and 2 receiver (2x2) multiple-input multiple-output (MIMO) system using zero forcing equalization. The script generates transmitted bits, applies BPSK modulation, sends the signals over a Rayleigh fading channel with additive noise, uses zero forcing equalization at the receiver, and compares the estimated and transmitted bits to calculate the simulated BER over a range of signal-to-noise ratio (SNR) values. The simulated results are then plotted along with theoretical BER curves for 1x1 and 2x2 MIMO systems.
Lab manualsahu[et&t]
This document contains 10 experiments on numerical analysis and C programming. Each experiment includes the aim, C code implementation, and sample output for programs that calculate sphere volume and area, sum of digits in a number, triangle property classification, checking for Pythagorean triplets, printing prime numbers within a range, calculating digit sum using a function, reversing an integer using recursion, summing even numbers recursively, sorting an array using bubble sort, and finding the intersection of values in two arrays.
04 - Scala. Type of natural numbers
This document discusses representations of natural numbers in programming languages like Haskell, Scala, and Java. It presents natural numbers as a type with two constructors: Zero and Suc. It also presents an eliminator and computation rules for reducing terms, as well as a uniqueness principle for natural numbers. Examples are given of defining and proving properties of functions over natural numbers using a proof assistant called ProvingGround.
Juan matlab
This document provides MatLab code examples for analyzing well log data, plotting seismic data, and performing a Fourier transform. It loads well log data, finds a specific formation within the well based on depth, and performs a regression to relate P-wave velocity and density using Gardner's equation. It also shows how to plot the well data, seismic data in different views, and discusses interfacing MatLab with other languages and Unix.
Pslb lab manual
The document contains 10 programming experiments involving basic C programming concepts like functions, arrays, loops, conditional statements, etc. Each experiment has the aim, code implementation, and sample output for programs to calculate sphere volume and area, sum of digits in a number, triangle properties, Pythagorean triplets, prime numbers in a range, recursive functions to reverse a number, sum even numbers, bubble sort an array, and find common elements between two arrays.
Lab loop
This document discusses different loop structures in C programming including for, while, and do-while loops. It provides 4 code examples, the first using a for loop to print numbers 1-10, the second manually printing the same using printfs, the third calculating a sum using a while loop, and the fourth calculating a factorial using a do-while loop. The document covers the basic syntax of these common loop structures.
C programs Set 2
This program uses recursive functions to:
1. Calculate the standard deviation of an array of values by calculating the mean, summing the squared differences from the mean, and taking the square root.
2. Find the factorial of a number by multiplying it by the factorial of the previous number down to 1.
3. Find the sum of odd numbers between a range by recursively adding each odd number.
matlab code for channel estimation for ofdm
This Matlab code simulates OFDM channel estimation using a PN sequence as a cyclic prefix. It generates transmitted OFDM signals, adds channel effects using different multipath delay profiles, and estimates the channel using three methods: conventional correlation, correlation with two-tap filter estimation, and interpolation of periodically inserted PN sequences. It compares the bit error rates of the three channel estimation methods under varying signal-to-noise ratios.
Anders Nielsen template model-builder
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Roots of a quadratic equation1
This C++ program allows a user to input the coefficients a, b, and c of a quadratic equation ax^2 + bx + c. It then calculates the two roots of the equation and displays them, assigning both roots a value of 0 if the equation results in complex roots. The program was written by Wilson on February 5, 2015.
Demodulate bpsk up
This function demodulates BPSK modulated signals. It takes in a signal, samples it based on the bit rate to extract individual bits. It uses the sampled signals and reference sine and cosine waves to calculate inphase and quadrature values to determine if each bit is a 1 or 0. It then plots the original signal, demodulated binary data and received binary values.
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8.2
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Matlab bode diagram_instructions
This document describes three methods for creating Bode plots of a transfer function in MATLAB:
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This document discusses different loop structures in C programming including for, while, and do-while loops. It provides 4 code examples, the first using a for loop to print numbers 1-10, the second manually printing the same using printfs, the third calculating a sum using a while loop, and the fourth calculating a factorial using a do-while loop. The document covers the basic syntax of these common loop structures.
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This function demodulates BPSK modulated signals. It takes in a signal, samples it based on the bit rate to extract individual bits. It uses the sampled signals and reference sine and cosine waves to calculate inphase and quadrature values to determine if each bit is a 1 or 0. It then plots the original signal, demodulated binary data and received binary values.
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3) Calculating an optimal operating point that minimizes total costs based on false accept and reject rates.
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A = zeros(n,n+1);
x1 = zeros(1,n);
A=[5 -2 3 -1;-3 9 1 2;2 -1 -7 3];
x1 = [0 0 0];
tol = input('Enter tolerance, tol: ');
m = input('Enter maximum number of iterations, m: ');
w = input('Enter the parameter w (omega): ');
k = 1;
while k <= m
err = 0;
for i = 1 : n
s = 0;
for j = 1 : n
s = s-A(i,j)*x1(j);
end
s = w*(s+A(i,n+1))/A(i,i);
if abs(s) > err
err = abs(s);
end
x1(i) = x1(i)+s;
end
if err <= tol
break;
else
k = k+1;
end
end
fprintf('The solution vector after %d iterations is :\n', k);
for i = 1 : n
fprintf(' %11.8f \n', x1(i));
end
%% Multigrid test case with visulization
% Author: Ben Beaudry
clc; clear; close all
load A_b.mat;
A = full(A); % Unsparce matrix to show full power of Multigrid
pre = 2; % Number of presmoothing iterations
post = 2; % Number of postsmoothing iterations
% cycle = 1; % Type of multigrid cycle (1=V-cycle, 2=W-cycle, 3=F-cycle)
smooth = 1; % Smoother type (1=Jacobi, 2=Gauss-Seidel)
grids = 5; % Max grids in cycle
maxit = 10; % Max iterations of solver
tol = 1e-02; % Tolerance of solver
%% Solvers
% solve directly
t=cputime;
x_D = A\b;
fprintf('Direct Solve Time: %g Seconds\n',cputime-t)
% V-Cycle
t=cputime;
[x_V,res_V,it_V] = multigrid(A,b,pre,post,1,smooth,grids,maxit,tol);
fprintf('V-Cycle Solve Time: %g Seconds\n',cputime-t)
% W-Cycle
t=cputime;
[x_W,res_W,it_W] = multigrid(A,b,pre,post,2,smooth,grids,maxit,tol);
fprintf('W-Cycle Solve Time: %g Seconds\n',cputime-t)
% F-Cycle
t=cputime;
[x_F,res_F,it_F] = multigrid(A,b,pre,post,3,smooth,grids,maxit,tol);
fprintf('F-Cycle Solve Time: %g Seconds\n',cputime-t)
% max it for iterative methods
it = 100;
% Gauss-Siedel
t=cputime;
L = tril(A);
U = triu(A,1);
x_G = zeros(length(b),1);
res_G= zeros(it,1);
for g = 1:it
x_G = L\(b-U*x_G);
r = b - A * x_G;
res_G(g) = norm(r);
if res_G(g) < tol
break;
end
end
fprintf('Gauss-Seidel Solve Time: %g Seconds\n',cputime-t)
% Jacobi
t=cputime;
d = diag(A);
dinv = 1./d;
LU = tril(A,-1)+triu(A,1);
U = triu(A,1);
x_J = zeros(length(b),1);
res_J= zeros(it,1);
for j = 1:it
x_J = dinv.*(b-(LU*x_J));
r = b - A * x_J;
res_J(j) = norm(r);
if res_J(j) < tol
break;
end
end
fprintf('Jacobi Solve Time: %g Seconds\n',cputime-t)
%% Plotting
figure;
hold on
plot(1:g,res_G(1:g),'o-','DisplayName','Guass-Seidel')
plot(1:j,res_J(1:j),'o-','DisplayName','Jacobi')
plot(1:it_V,res_V(1:it_V),'o-','DisplayName','V-Cycle Multigrid')
plot(1:it_F,res_F(1:it_F),'o-','DisplayName','F-Cycle Multigrid')
plot(1:it_W,res_W(1:it_W),'o-','DisplayName','W-Cycle Multigrid')
set(gca,'XLim',[0 100]);
grid on
legend('location','best')
ylabel('Relative Convergance')
xlabel('Iterations')
title('Convergance of Numerical System')
hold off
MULTIGRID FUNC.
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Newconceptdataanalyze
- 1. %consts vtransverse=590; %origin gamma=1; %experimental data load('C:Program FilesMatlabdatadata1Bb.dat'); load('C:Program FilesMatlabdatadata1rb.dat'); load('C:Program FilesMatlabdatadata1R.dat'); time=clock;starttime=(60*time(5)+time(6)); dr=0.001;%new advanced bracket r = 0:dr:R; n=(R/dr)+1; root1=zeros(1,n); root2=zeros(1,n); M=10; %max degree of fitted polynom B Bint=interp1(rb,Bb,r,'spline'); B=polyfit(r,Bint,M); %It ain't a simple MASSIVE A=zeros(1,M+2); for i=1:1:M+1 A(i)=B(i)/(M-i+3); end A(M+2)=0; C=zeros(1,M+3); for i=1:1:M+1 C(i)=gamma*A(i); end C(M+2)=-1; %Solving the first kind equation (root1) for i=1:1:n rcur=r(i); Acur=polyval(A,rcur); const=rcur*(gamma*Acur+1); C(M+3)=-const; preroot=roots(C); for j=1:1:numel(preroot) if ((real(preroot(j))>0) && (real(preroot(j))<R) && (imag(preroot(j))==0)) root1(i)=preroot(j); end end if (root1(i)==0) root1(i)=R; end end %Solving the second kind equation (root2) for i=1:1:n rcur=r(i); Acur=polyval(A,rcur); const=rcur*(gamma*Acur-1); C(M+3)=-const; preroot=roots(C);
- 2. for j=1:1:numel(preroot) if ((real(preroot(j))>0) && (real(preroot(j))<R) && (imag(preroot(j))==0) && (real(preroot(j))>r(i))) if (root2(i)<real(preroot(j))) root2(i)=preroot(j); end end end if (root2(i)==0) root2(i)=r(i); end end time=clock;endtime=60*time(5)+time(6); figure(5);plot(r,root1,'bluex',r,root2,'redx');grid on;title(num2str(endtime- starttime));