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bilinear transform : ウィキペディア英語版
bilinear transform

The bilinear transform (also known as Tustin's method) is used in digital signal processing and discrete-time control theory to transform continuous-time system representations to discrete-time and vice versa.
The bilinear transform is a special case of a conformal mapping (namely, the Möbius transformation), often used to convert a transfer function H_a(s) \ of a linear, time-invariant (LTI) filter in the continuous-time domain (often called an analog filter) to a transfer function H_d(z) \ of a linear, shift-invariant filter in the discrete-time domain (often called a digital filter although there are analog filters constructed with switched capacitors that are discrete-time filters). It maps positions on the j \omega \ axis, Re()=0 \ , in the s-plane to the unit circle, |z| = 1 \ , in the z-plane. Other bilinear transforms can be used to warp the frequency response of any discrete-time linear system (for example to approximate the non-linear frequency resolution of the human auditory system) and are implementable in the discrete domain by replacing a system's unit delays \left( z^ \right) \ with first order all-pass filters.
The transform preserves stability and maps every point of the frequency response of the continuous-time filter, H_a(j \omega_a) \ to a corresponding point in the frequency response of the discrete-time filter, H_d(e^) \ although to a somewhat different frequency, as shown in the Frequency warping section below. This means that for every feature that one sees in the frequency response of the analog filter, there is a corresponding feature, with identical gain and phase shift, in the frequency response of the digital filter but, perhaps, at a somewhat different frequency. This is barely noticeable at low frequencies but is quite evident at frequencies close to the Nyquist frequency.
== Discrete-time approximation ==
The bilinear transform is a first-order approximation of the natural logarithm function that is an exact mapping of the ''z''-plane to the ''s''-plane. When the Laplace transform is performed on a discrete-time signal (with each element of the discrete-time sequence attached to a correspondingly delayed unit impulse), the result is precisely the Z transform of the discrete-time sequence with the substitution of
:
\begin
z &= e^ \\
&= \frac} \\
&\approx \frac
\end

where T \ is the numerical integration step size of the trapezoidal rule used in the bilinear transform derivation; or, in other words, the sampling period. The above bilinear approximation can be solved for s \ or a similar approximation for s = (1/T) \ln(z) \ \ can be performed.
The inverse of this mapping (and its first-order bilinear approximation) is
:
\begin
s &= \frac \ln(z) \\
&= \frac \left(+ \frac \left( \frac \right)^3 + \frac \left( \frac \right)^5 + \frac \left( \frac \right)^7 + \cdots \right ) \\
&\approx \frac \frac \\
&= \frac \frac}
\end

The bilinear transform essentially uses this first order approximation and substitutes into the continuous-time transfer function, H_a(s) \
:s \leftarrow \frac \frac.
That is
:H_d(z) = H_a(s) \bigg|_ \frac}= H_a \left( \frac \frac \right). \

抄文引用元・出典: フリー百科事典『 ウィキペディア(Wikipedia)
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