| Symbolic Math |
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💡 syms |
Define symbolic variables for algebraic manipulations. |
Example: syms x y |
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💡 solve |
Solve algebraic equations symbolically. |
Example: eqn = x^2 - 4*x + 4 == 0;
sol = solve(eqn, x); |
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💡 diff |
Compute derivatives symbolically. |
Example: f = x^2 + 2*x + 1;
df = diff(f, x); |
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💡 int |
Compute integrals symbolically. |
Example: f = x^2 + 2*x + 1;
F = int(f, x); |
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| Numeric Calculations |
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💡 sum |
Calculate the sum of elements in an array. |
Example: A = [1, 2, 3, 4, 5];
total = sum(A); |
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💡 prod |
Calculate the product of elements in an array. |
Example: A = [1, 2, 3, 4, 5];
product = prod(A); |
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💡 mean |
Compute the mean (average) of data. |
Example: data = [75, 80, 85, 90, 95];
avg = mean(data); |
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💡 std |
Calculate the standard deviation of data. |
Example: data = [75, 80, 85, 90, 95];
deviation = std(data); |
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| Plotting |
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💡 plot |
Create 2D plots of data. |
Example: x = linspace(0, 2*pi, 100);
y = sin(x);
plot(x, y); |
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💡 ezplot |
Create plots of symbolic expressions. |
Example: syms x
f = x^2 - 4*x + 4;
ezplot(f); |
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| Linear Algebra |
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💡 inv |
Compute the inverse of a matrix. |
Example: A = [1, 2; 3, 4];
B = inv(A); |
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💡 det |
Calculate the determinant of a matrix. |
Example: A = [1, 2; 3, 4];
determinant = det(A); |
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| Numerical Methods |
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💡 fminunc |
Find the minimum of a function numerically. |
Example: fun = @(x) x^2 - 4*x + 4;
x0 = 0; % Initial guess
xmin = fminunc(fun, x0); |
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💡 ode45 |
Solve ordinary differential equations (ODEs). |
Example: dydt = @(t, y) -2*y;
[t, y] = ode45(dydt, [0, 5], 1); |
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| Statistics |
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💡 normpdf |
Compute the probability density function of a normal distribution. |
Example: mu = 0; % Mean
sigma = 1; % Standard deviation
x = -3:0.1:3;
pdf = normpdf(x, mu, sigma); |
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💡 binopdf |
Compute the probability mass function of a binomial distribution. |
Example: n = 10; % Number of trials
p = 0.5; % Probability of success
k = 0:10;
pmf = binopdf(k, n, p); |
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