In contradistinction, a linear, non-minimum phase transfer function can be modeled as minimum phase transfer function in series with an all-pass-filter, the characteristic issue of that series combination will be zeroes in the right-half-plane. A consequence of zeroes in the right-half-plane, is that the inverted function is not stable. The all pass filter (can also be transport delay) inserts 'excess phase', that is why the resulting function would be non-minimum phase.
For example, a discrete-time system with rationaltransfer function can only satisfy causality and stability requirements if all of its poles are inside the unit circle. However, we are free to choose whether the zeros of the system are inside or outside the unit circle. A system with rational transfer function is minimum-phase if all its zeros are also inside the unit circle. Insight is given below as to why this system is called minimum-phase.
A system is invertible if we can uniquely determine its input from its output. I.e., we can find a system such that if we apply followed by , we obtain the identity system . (See Inverse matrix for a finite-dimensional analog). I.e.,
Suppose that is input to system and gives output .
Applying the inverse system to gives the following.
So we see that the inverse system allows us to determine uniquely the input from the output .
Suppose that the system is a discrete-time, linear, time-invariant (LTI) system described by the impulse response for n in Z. Additionally, suppose has impulse response . The cascade of two LTI systems is a convolution. In this case, the above relation is the following:
where is the Kronecker delta or the identity system in the discrete-time case. Note that this inverse system need not be unique.
When we impose the constraints of causality and stability, the inverse system is unique; and the system and its inverse are called minimum-phase. The causality and stability constraints in the discrete-time case are the following (for time-invariant systems where h is the system's impulse response):
where A (z) and D (z) are polynomial in z. Causality and stability imply that the poles – the roots of D (z) – must be strictly inside the unit circle. We also know that
So, causality and stability for imply that its poles – the roots of A (z) – must be inside the unit circle. These two constraints imply that both the zeros and the poles of a minimum phase system must be strictly inside the unit circle.
where A (s) and D (s) are polynomial in s. Causality and stability imply that the poles – the roots of D (s) – must be inside the left-half s-plane. We also know that
So, causality and stability for imply that its poles – the roots of A (s) – must be strictly inside the left-half s-plane. These two constraints imply that both the zeros and the poles of a minimum phase system must be strictly inside the left-half s-plane.
Relationship of magnitude response to phase response
A minimum-phase system, whether discrete-time or continuous-time, has an additional useful property that the natural logarithm of the magnitude of the frequency response (the "gain" measured in nepers which is proportional to dB) is related to the phase angle of the frequency response (measured in radians) by the Hilbert transform. That is, in the continuous-time case, let
be the complex frequency response of system H(s). Then, only for a minimum-phase system, the phase response of H(s) is related to the gain by
Stated more compactly, let
where and are real functions of a real variable. Then
The Hilbert transform operator is defined to be
An equivalent corresponding relationship is also true for discrete-time minimum-phase systems.
The denominator and are invariant to reflecting the zero outside of the unit circle, i.e., replacing with . However, by reflecting outside of the unit circle, we increase the magnitude of in the numerator. Thus, having inside the unit circle minimizes the group delay contributed by the factor . We can extend this result to the general case of more than one zero since the phase of the multiplicative factors of the form is additive. I.e., for a transfer function with zeros,
Illustration of the calculus above. Top and bottom are filters with same gain response (on the left : the Nyquist diagrams, on the right : phase responses), but the filter on the top with has the smallest amplitude in phase response.
Systems that are causal and stable whose inverses are causal and unstable are known as non-minimum-phase systems. A given non-minimum phase system will have a greater phase contribution than the minimum-phase system with the equivalent magnitude response.
A maximum-phase system is the opposite of a minimum phase system. A causal and stable LTI system is a maximum-phase system if its inverse is causal and unstable.[dubious– discuss] That is,
The zeros of the discrete-time system are outside the unit circle.
The zeros of the continuous-time system are in the right-hand side of the complex plane.
Such a system is called a maximum-phase system because it has the maximum group delay of the set of systems that have the same magnitude response. In this set of equal-magnitude-response systems, the maximum phase system will have maximum energy delay.
For example, the two continuous-time LTI systems described by the transfer functions
have equivalent magnitude responses; however, the second system has a much larger contribution to the phase shift. Hence, in this set, the second system is the maximum-phase system and the first system is the minimum-phase system.
A mixed-phase system has some of its zeros inside the unit circle and has others outside the unit circle. Thus, its group delay is neither minimum or maximum but somewhere between the group delay of the minimum and maximum phase equivalent system.
For example, the continuous-time LTI system described by transfer function
is stable and causal; however, it has zeros on both the left- and right-hand sides of the complex plane. Hence, it is a mixed-phase system.