Before we learn about properties of DFT first we learn about the exact meaning terms of DFT. The Fourier transform can be used for the analysis of a signal. It used for transformation from the time domain to the frequency domain. Here this article gives information about properties of DFT to know more details or learn about DFT

**.**

**Linearity :**

Periodic signals : A x(n) + B y(n)

Fourier series coefficients : A a

_{k}+ B b_{k}

**Time shifting :**
Periodic signals : x(n - n

Fourier series coefficients: a

_{0})Fourier series coefficients: a

_{k}e^{-jk(2π/N)n }

**Frequency Shifting :**
Periodic signals : x(n) e

^{jm(2π/N)n }
Fourier series coefficients : X(k - m)

**Conjugation :**

Periodic signals : x*(n)

^{ }
Fourier series coefficients :

^{a*}_{-k}

**Time Reversal :**

Periodic signals : x(-n)

Fourier series coefficients :

^{ }Fourier series coefficients :

^{a}_{-k}
Before we learn about properties of DFT first we learn about the exact meaning terms of DFT. The Fourier transform can be used for the analysis of a signal. It used for transformation from the time domain to the frequency domain. Here this article gives information about properties of DFT to know more details or learn about DFT

**.**

**Linearity :**

Periodic signals : A x(n) + B y(n)

Fourier series coefficients : A a

_{k}+ B b_{k}

**Time shifting :**
Periodic signals : x(n - n

Fourier series coefficients: a

_{0})Fourier series coefficients: a

_{k}e^{-jk(2π/N)n }

**Frequency Shifting :**
Periodic signals : x(n) e

^{jm(2π/N)n }
Fourier series coefficients : X(k - m)

**Conjugation :**

Periodic signals : x*(n)

^{ }
Fourier series coefficients :

^{a*}_{-k}

**Time Reversal :**

Periodic signals : x(-n)

Fourier series coefficients :

^{ }Fourier series coefficients :

^{a}_{-k}