X(f) = ∫[−T/2, T/2] e^-j2πftdt
The gradient of the cost function is:
4.1 : Minimize the cost function J(x) = x^2 + 2x + 1 using gradient descent.
For a Gaussian distribution, the Fourier transform is also Gaussian:
X(f) = ∫[−T/2, T/2] e^-j2πftdt
The gradient of the cost function is:
4.1 : Minimize the cost function J(x) = x^2 + 2x + 1 using gradient descent.
For a Gaussian distribution, the Fourier transform is also Gaussian: