- Trending Categories
- Data Structure
- Networking
- RDBMS
- Operating System
- Java
- iOS
- HTML
- CSS
- Android
- Python
- C Programming
- C++
- C#
- MongoDB
- MySQL
- Javascript
- PHP

- Selected Reading
- UPSC IAS Exams Notes
- Developer's Best Practices
- Questions and Answers
- Effective Resume Writing
- HR Interview Questions
- Computer Glossary
- Who is Who

A system for which the principle of superposition and the principle of homogeneity are valid and the input/output characteristics do not with time is called the *linear time invariant (LTI) system.*

A continuous-time LTI system can be represented in terms of its *unit impulse
response.* It takes the form of convolution integral. Hence, the properties followed by the continuous time convolution are also followed by the LTI system. The impulse response of an LTI system is very important because it can completely determine the characteristics of an LTI system.

In this article, we will highlight some of the important properties of an LTI system (or continuous-time convolution).

**Commutative Property of LTI System**

The convolution in continuous-time is a commutative operation, i.e.,

$$\mathrm{x(t)*h(t)=h(t)*x(t)=\int_{-\infty }^{\infty}x(\tau)\:h(t-\tau )d\tau=\int_{-\infty }^{\infty}h(\tau)\:x(t-\tau )d\tau}$$

Therefore, according to the commutative property of an LTI system, the output of the LTI system with input x(t) and unit impulse response h(t) is same as the output of the LTI system with input h(t) and impulse response x(t).

**Distributive Property of LTI System**

The convolution in continuous-time distributes over addition, i.e.,

$$\mathrm{x(t)*[h_{1}(t)+h_{2}(t)]=x(t)*h_{1}(t)+x(t)*h_{2}(t)}$$

The distributive property of the LTI system has a useful interpretation in terms of system interconnection. Hence, according to this, the two LTI systems with impulse responses $h_{1}(t)$ and $h_{2}(t)$ connected in parallel can be replaced by a single system with impulse response [$h_{1}(t)+h_{2}(t)]$. Also, the distributive property of continuous-time convolution can be used to break a complicated convolution into several simpler convolutions.

**Associative Property of LTI System**

The convolution in continuous-time is associative, i.e.,

$$\mathrm{x(t)*[h_{1}(t)*h_{2}(t)]=[x(t)*h_{1}(t)]*h_{2}(t)}$$

Therefore, according to the associative property the signals can be convolved in any order.

**Causality Property of LTI System**

A causal system is non-anticipatory and does not produce an output before an input is applied. Therefore, the output of a causal system depends only on the present and past values of input but not on the future inputs.

Hence, for a causal LTI system, we get,

$$\mathrm{h(t)=0;\:for\:t<0}$$

Therefore,

The output of a causal LTI system for a non-causal input is given by,

$$\mathrm{y(t)=\int_{0}^{\infty }h(\tau )\:x(t-\tau)d\tau=\int_{-\infty}^{t}x(\tau)\:h(t-\tau)d\tau}$$

The output of a causal LTI system for a causal input is given by,

$$\mathrm{y(t)=\int_{0}^{t}h(\tau )\:x(t-\tau)d\tau=\int_{0}^{t}x(\tau )\: h(t-\tau)d\tau}$$

If for a given system every bounded input produces a bounded output, then the system is stable. The stability of an LTI system can be determined from its impulse response. For a continuous-time LTI system to be stable, its impulse response h(t) must be absolutely integrable, i.e.,

$$\mathrm{\int_{-\infty }^{\infty}\left | h(\tau )\right |d\tau<\infty}$$

**Invertibility of LTI System**

A continuous LTI system with impulse response is called invertible, if an inverse system with impulse response ${h}'(t)$ which when connected in series with the original system produces an output equal to the input of the first system, i.e.,

$$\mathrm{h(t)*{h}'(t)=\delta(t)}$$

**LTI System with and without Memory**

An LTI system is called static or memoryless system if its output at any time depends only upon the value of the input at that time. Hence, a continuous-time LTI system is said to be memoryless system if,

$$\mathrm{h(t)=0;\:for\:t\neq0}$$

Such a memoryless LTI system is represented as,

$$\mathrm{y(t)=k\:x(t)}$$

The system has some memory if,

$$\mathrm{h(t)\neq0;\:for\:t\neq0}$$

The memory system is also known as *dynamic system.*

**Unit Step Response of LTI System**

When the unit step input u(t) is applied to an LTI system, then the corresponding output is called the unit step response s(t) of the LTI system.

The unit step response of an LTI system can be obtained by convolving the unit step input u(t) with the impulse response h(t) of the system, i.e.

$$\mathrm{s(t)=u(t)*h(t)=h(t)*u(t)}$$

$$\mathrm{\Rightarrow s(t)=\int_{-\infty }^{t}h(\tau)d\tau}$$

- Related Questions & Answers
- Signals and Systems – Response of Linear Time Invariant (LTI) System
- Signals and Systems – Transfer Function of Linear Time Invariant (LTI) System
- Signals and Systems: Linear Time-Invariant Systems
- Signals and Systems: Time Variant and Time-Invariant Systems
- Signals and Systems – Filter Characteristics of Linear Systems
- Signals and Systems: Linear and Non-Linear Systems
- Signals and Systems – Properties of Discrete-Time Fourier Transform
- Signals and Systems – Time Scaling of Signals
- Signals and Systems – Properties of Even and Odd Signals
- Signals and Systems – Properties of Laplace Transform
- Signals & Systems – Properties of Continuous Time Fourier Series
- Signals and Systems – Classification of Signals
- Signals and Systems – What is a Linear System?
- Properties of Convolution in Signals and Systems
- Signals and Systems: Classification of Systems

Advertisements