How does Matlab calculate pulse width?
w = pulsewidth( x ) returns the time differences between the midreference level instants of the initial and final transitions of each positive-polarity pulse in the input bilevel waveform. w = pulsewidth( x , fs ) specifies the sample rate fs in hertz. The first sample in the waveform corresponds to t = 0.
How do you use Tripuls in Matlab?
y = tripuls( t ) returns a continuous, aperiodic, symmetric, unit-height triangular pulse at the sample times indicated in array t , centered about t = 0 . y = tripuls( t , w , s ) generates a triangle of width w and skew s .
How do you make a triangular pulse in Matlab?
Special Cases of Triangular Pulse Function
- syms a b x. Compute the triangular pulse function for b < x < c :
- syms b c x. Compute the triangular pulse function for a = b :
- ans = -((c – x)*rectangularPulse(b, c, x))/(b – c) Compute the triangular pulse function for c = b :
- ans = ((a – x)*rectangularPulse(a, b, x))/(a – b)
How do you find your pulse width?
Create a ratio that places the length of the cycle activity in the numerator and the length of the overall cycle in the denominator. Divide the numbers. Multiply the result by 100 percent. This yields the pulse width of the duty cycle.
How do you write triangular functions in Matlab?
If a < x < b , then the triangular pulse function equals (x – a)/(b – a) . If b < x < c , then the triangular pulse function equals (c – x)/(c – b) . If x <= a or x >= c , then the triangular pulse function equals 0.
How do I implement a logistic regression model?
In order to implement a logistic regression model, I usually call the glmfit function, which is the simpler way to go. The syntax is:
How do I make predictions using my learned logistic regression parameters?
function p = predict (theta, X) % Instructions: Complete the following code to make predictions using % your learned logistic regression parameters. % You should set p to a vector of 0’s and 1’s % h = sigmoid (X * theta); p = round (h); end
How do you calculate sigmoid in logistic regression?
function g = sigmoid (z) g = zeros (size (z)); # Compute the sigmoid of each value of z (z can be a matrix, vector or scalar). g = 1 ./ (1 + exp (-z)) end Implement the cost function and gradient for logistic regression.
How many natural numbers can be used in logistic regression?
Nominal Logistic Regression is quite wide as dependent variable could take more than 2 values, but they have to be consecutive natural numbers. For example Y = 0, 1, 2, 3, X, the independent variable doesn’t have this restriction it can be any reel number.