Detection of Periodic Signals in the Presence of NoiseThe noise signal is an unwanted signal which has random amplitude variation. The noise signals are uncorrelated with any periodic signal.Detection of the periodic signals masked by noise signals is of great importance in signal processing. It is mainly used in the detection of radar and sonar signals, the detection of periodic components in brain signals, in the detection of periodic components in sea wave analysis and in many other areas of geophysics etc. The solution of these problems can be easily provided by the correlation techniques. The autocorrelation function, therefore can ... Read More

Cross Correlation FunctionThe cross correlation function between two different signals is defined as the measure of similarity or coherence between one signal and the time delayed version of another signal.The cross correlation function is defined separately for energy (or aperiodic) signals and power or periodic signals.Cross Correlation of Energy SignalsConsider two energy signals $\mathit{x_{\mathrm{1}}}\mathrm{(\mathit{t})}$ and $\mathit{x_{\mathrm{2}}}\mathrm{(\mathit{t})}$. The cross correlation of these two energy signals is defined as −

$$\mathit{R_{\mathrm{12}}}\mathrm{(\tau)}\:\mathrm{=}\:\int_{-\infty}^{\infty}\mathit{x_{\mathrm{1}}}\mathrm{(\mathit{t})}x_{\mathrm{2}}^{*}\mathrm{(\mathit{t-\tau})}\mathit{dt} \:\mathrm{=}\: \int_{-\infty}^{\infty}\mathit{x_{\mathrm{1}}}\mathrm{(\mathit{t+\tau})}\mathit{x_\mathrm{2}^*}\mathrm{(\mathit{t})}\mathit{dt}$$ Where, the variable $\tau$ is called the delay parameter or scanning parameter or searching parameter.The cross correlation of two energy signals is defined in another form as − $$\mathit{R_{\mathrm{12}}}\mathrm{(\mathit{\tau})} \:\mathrm{=}\: \int_{-\infty}^{\infty}\mathit{x_\mathrm{2}}\mathrm{(t)}\mathit{x_\mathrm{1}^*}\mathrm{(t-\tau)}\:\mathit{dt}$$ Properties of ... Read More

Autocorrelation FunctionThe autocorrelation function defines the measure of similarity or coherence between a signal and its time delayed version. The autocorrelation function of a real energy signal $\mathit{x}\mathrm{(\mathit{t})}$ is given by,

$$\mathit{R}\mathrm{(\mathit{\tau})} \:\mathrm{=}\: \int_{-\infty}^{\infty}\mathit{x\mathrm(\mathit{t})}\:\mathit{x}\mathrm{(\mathit{t-\tau})}\:\mathit{dt}$$ Energy Spectral Density (ESD) FunctionThe distribution of the energy of a signal in the frequency domain is called the energy spectral density.The ESD function of a signal is given by, $$\mathit{\psi}\mathrm{(\mathit{\omega})}\: \mathrm{=}\: \mathrm{|\mathit{X}\mathrm{(\mathit{\omega})}|}^\mathrm{2} \:\mathrm{=}\: \mathit{X}\mathrm{(\mathit{\omega})} \mathit{X}\mathrm{(\mathit{-\omega})}$$ Autocorrelation TheoremStatement − The autocorrelation theorem states that the autocorrelation function $\mathit{R}\mathrm{(\mathrm{\tau})}$ and the ESD (Energy Spectral Density) function $\mathit{\psi}\mathrm{(\mathit{\omega})}$ of an energy signal $\mathit{x}\mathrm{(\mathit{t})}$ form a Fourier transform pair, i.e., $$\mathit{R}\mathrm{(\mathit{\tau})} ... Read More

Energy Spectral DensityThe distribution of the energy of a signal in the frequency domain is known as energy spectral density (ESD) or energy density (ED) or energy density spectrum. The ESD function is denoted by $\mathrm{\mathit{\psi \left ( \omega \right )}}$ and is given by,

$$\mathrm{\mathit{\psi \left ( \omega \right )\mathrm{=}\left|X\left ( \omega \right ) \right|^{\mathrm{2}}}}$$ For an energy signal, the total area under the energy spectral density curve plotted as the function of frequency is equal to the total energy of the signal.ExplanationConsider a linear system having $\mathrm{\mathit{x\left ( \mathit{t} \right )}}$ and $\mathrm{\mathit{y\left ( \mathit{t} \right )}}$ as input ... Read More

What is Autocorrelation?The autocorrelation function of a signal is defined as the measure of similarity or coherence between a signal and its time delayed version. Thus, the autocorrelation is the correlation of a signal with itself.The autocorrelation function is defined separately for energy or aperiodic signals and power or periodic signals.Autocorrelation Function for Energy SignalsThe autocorrelation function of an energy signal $\mathrm{\mathit{x\left ( \mathit{t} \right )}}$ is defined as −$$\mathrm{\mathit{R_{\mathrm{11}}\left ( \tau \right )\mathrm{=}R\left ( \tau \right )\mathrm{=}\int_{-\infty }^{\infty }x\left ( t \right )x^{\ast }\left ( t-\tau \right )dt\mathrm{=}\int_{-\infty }^{\infty }x\left ( t\mathrm{+ }\tau \right )x^{\ast }\left ( t \right ... Read More

Laplace TransformThe Laplace transform is a mathematical tool which is used to convert the differential equation in time domain into the algebraic equations in the frequency domain or s-domain.Mathematically, if $\mathrm{\mathit{x\left ( \mathit{t} \right )}}$ is a time domain function, then its Laplace transform is defined as,

$$\mathrm{\mathit{L\left [ x\left ( \mathrm{t} \right ) \right ]}\mathrm{=} \mathit{X\left ( s \right )}\mathrm{=}\int_{-\infty }^{\infty}\mathit{x\left ( \mathrm{t} \right )e^{-st}\; dt}\; \; ...\left ( 1 \right )}$$ Equation (1) gives the bilateral Laplace transform of the function $\mathrm{\mathit{x\left ( \mathit{t} \right )}}$. But for the causal signals, the unilateral Laplace transform is applied, which is ... Read More

Laplace TransformThe Laplace transform is a mathematical tool which is used to convert the differential equations in time domain into the algebraic equations in the frequency domain or s-domain.Mathematically, if $\mathrm{\mathit{x\left ( \mathit{t} \right )}}$ is a time domain function, then its Laplace transform is defined as −

$$\mathrm{\mathit{L\left [ x\left ( \mathrm{t} \right ) \right ]}\mathrm{=} \mathit{X\left ( s \right )}\mathrm{=}\int_{-\infty }^{\infty}\mathit{x\left ( \mathrm{t} \right )e^{-st}\; dt}\; \; ...\left ( 1 \right )}$$ Where, 𝑠 is a complex variable and it is given by, $$\mathrm{s = \sigma + j\omega }$$ And the operator L is called the Laplace transform operator which transforms ... Read More

Laplace TransformThe linear time invariant (LTI) system is described by differential equations. The Laplace transform is a mathematical tool which converts the differential equations in time domain into algebraic equations in the frequency domain (or s-domain).If $\mathrm{\mathit{x\left ( t \right )}}$ is a time function, then the Laplace transform of the function is defined as −

$$\mathrm{\mathit{L\left [ x\left ( t \right ) \right ]\mathrm{=}X\left ( s \right )\mathrm{=}\int_{-\infty }^{\infty }x\left ( t \right )e^{-st}\:dt\; \; \cdot \cdot \cdot\left ( \mathrm{1} \right ) }}$$ Where, s is a complex variable and it is given by, $$\mathrm{\mathit{s\mathrm{=}\sigma \mathrm{+ }j\omega }}$$ Inverse Laplace TransformThe inverse ... Read More

Z-TransformThe Z-transform (ZT) is a mathematical tool which is used to convert the difference equations in time domain into the algebraic equations in z-domain.Mathematically, if $\mathit{x}\mathrm{\left(\mathit{n}\right)}$ is a discrete-time signal or sequence, then its bilateral or two-sided Z-transform is defined as −

$$\mathrm{\mathit{Z}\mathrm{\left[\mathit{x}\mathrm{\left(\mathit{n}\right)}\right]}\:\mathrm{=}\:\mathit{X}\mathrm{\left(\mathit{z}\right)}\:\mathrm{=}\:\sum_{\mathit{n=-\infty}}^{\infty}\mathit{x}\mathrm{\left(\mathit{n}\right)}\mathit{z^{-\mathit{n}}}\:\:\:\:\:\:...(1)}$$ Where, z is a complex variable.Also, the unilateral or one-sided z-transform is defined as − $$\mathrm{\mathit{Z}\mathrm{\left[\mathit{x}\mathrm{\left(\mathit{n}\right)}\right]}\:\mathrm{=}\:\mathit{X}\mathrm{\left(\mathit{z}\right)}\:\mathrm{=}\:\sum_{\mathit{n=\mathrm{0}}}^{\infty}\mathit{x}\mathrm{\left(\mathit{n}\right)}\mathit{z^{-\mathit{n}}}\:\:\:\:\:\:...(2)}$$ Laplace TransformThe Laplace transform is a mathematical tool which is used to convert the differential equation in time domain into the algebraic equations in the frequency domain or s-domain.Mathematically, if $\mathit{x}\mathrm{\left(\mathit{t}\right)}$ is a continuous-time function, then its Laplace transform is defined as − $$\mathrm{\mathit{L}\mathrm{\left[\mathit{x}\mathrm{\left(\mathit{t}\right)}\right]}\:\mathrm{=}\:\mathit{X}\mathrm{\left(\mathit{s}\right)}\:\mathrm{=}\:\int_{-\infty }^{\infty }\mathit{x}\mathrm{\left(\mathit{t}\right)}\mathit{e^{-\mathit{st}}\:\mathit{dt}}\:\:\:\:\:\:...(3)}$$ Equation ... Read More

Discrete-Time Fourier TransformThe Fourier transform of the discrete-time signals is known as the discrete-time Fourier transform (DTFT). The DTFT converts a time domain sequence into frequency domain signal. The DTFT of a discrete time sequence $\mathit{x}\mathrm{\left(\mathit{n}\right)}$ is given by,

$$\mathrm{\mathit{F}\mathrm{\left[\mathit{x}\mathrm{\left(\mathit{n}\right)}\right]}\:\mathrm{=}\:\mathit{X}\mathrm{\left(\mathit{\omega}\right)}\:\mathrm{=}\:\sum_{\mathit{n=-\infty}}^{\infty}\mathit{x}\mathrm{\left(\mathit{n}\right)}\mathit{e^{-j\omega n}}\:\:\:\:\:\:...(1)}$$ Z-TransformThe Z-transform is a mathematical which is used to convert the difference equations in time domain into the algebraic equations in z-domain. Mathematically, the Z-transform of a discrete time sequence $\mathit{x}\mathrm{\left(\mathit{n}\right)}$ is given by, $$\mathrm{\mathit{Z}\mathrm{\left[\mathit{x}\mathrm{\left(\mathit{n}\right)}\right]}\:\mathrm{=}\:\mathit{X}\mathrm{\left(\mathit{z}\right)}\:\mathrm{=}\:\sum_{\mathit{n=-\infty}}^{\infty}\mathit{x}\mathrm{\left(\mathit{n}\right)}\mathit{z^{-\mathit{n}}}\:\:\:\:\:\:...(2)}$$ Relation between DTFT and Z-TransformSince the DTFT of a discrete time sequence $\mathit{x}\mathrm{\left(\mathit{n}\right)}$ is given by, $$\mathrm{\mathit{X}\mathrm{\left(\mathit{\omega }\right)}\:\mathrm{=}\:\sum_{\mathit{n=-\infty}}^{\infty}\mathit{x}\mathrm{\left(\mathit{n}\right)}\mathit{e^{-\mathit{j\omega n}}}\:\:\:\:\:\:...(3)}$$ For the existence of the DTFT, the sequence ... Read More