Linear and Non linear system
• A system is said to be linear if it satisfies the superposition principle.
• Superposition principle states that the response to a weighted sum of input signal be equal to the weighted sum of the output corresponding to each of the individual input signal
• The continuous system is linear if,
F[a1x1(t) + a2x2(t)] = a1y1(t) + a2y2(t)
• The discrete system is linear if, F[a1x1(n) + a2x2(n)] = a1y1(n) + a2y2(n)
• Otherwise the system is non linear.
• A system is called linear if its I/O behavior satisfies the additivity and homogeneity propertiesCausal and Non causal system
• A causal system is one whose output depends upon the present and past input values.
• If the system depends the future input values, the system is said to be non causal.
Eg. for causal system.
Y(t) = x(t) + x(t - 1)
Y(n) = x(n) + x(n - 3)
Eg. For non causal system,
Y(t) = x(t+3) + x2(t)
Y(n) = x(2n)
• A system is called causal or non-anticipative if the output at any time t (or n) depends only on the input at times t or before t (or n or before n); in other words, independent of the input at times after t (or n). All memory less systems are causal. Physical systems where the time is the independent variable are causal.
• Non-causal systems may arise in applications where the independent variable is not the time such as in the image processing applications.• When every bounded input produces bounded output then the system is called as
stable system or bounded input bounded output (BIBO stable).
• Otherwise the system is unstable.
• A system is called stable if it produces bounded outputs for all bounded inputs.
• Stability in a physical system generally results from the presence of mechanisms that dissipate energy, such as the resistors in a circuit, friction in a mechanical system, etc.
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