Discrete-Time Fractional Difference Calculus: Origins, Evolutions, and New Formalisms
Abstract
:1. Introduction
2. Preliminaries
2.1. Glossary and Assumptions
- Anti-causal [36]An anti-causal system is causal under reverse time flow. A system is anti-causal if the output at any instant depends only on values of the input and/or output at the present and future time instants. The delta derivative is an example of an anti-causal system.
- Anti-differenceThe operator that is simultaneously the left and right inverse of the difference will be called anti-difference.
- BackwardReverse time flow—from future to past.
- A system is causal if the output at any instant depends only on the values of the input and/or output at the present and past instants. The nabla derivative is an example of a causal system.
- ForwardNormal time flow—from past to future.
- FractionalFractional will have the meaning of a non-integer real number.
- Scale-invariant system
- SignalBounded function that conveys some kind of information.
- Shift-invariant systemA system is shift-invariant if a delay or lead in the input produces the same delay/lead in the output. It is described by the usual convolution [37]
- Any operator that transforms signals into signals. We will often use the terms system and operator interchangeably.
2.2. Some Mathematical Tools
2.3. On Time Sequences
2.4. On the Sampling
3. Historical Overview
3.1. Euler Procedure
3.2. Differences and Fractional Calculus
3.3. Discrete-Time Differences
4. A Critical View of Some Aspects Related to Differences
4.1. A “Fractional Delta Difference” that Is Not a Delta Difference
- Order 1 differenceFor a given t, the difference depends on the present and future values.
- Order differenceAgain, for a given t, the -order difference (sum) depends on the present and future values.
- Order differencewith , we haveContrarily to the above examples, the -order derivative depends on one future value and infinite past values. Therefore, an operator that we were expected to be anti-causal is essentially causal.
4.2. One for All or One for Each
- expresses a situation where there is a past and a future. It is like some system that exists, is in stand-by first, acts for some time, and returns to the previous state. It is the situation corresponding to many physical, biological, and social systems.
- , on the contrary, has no past and will have no future: something is born, lives for some time and disappears.
4.3. The Riemann–Liouvile and Caputo-like Procedures
- We throw most of the computational burden on negative-order binomial coefficients that behave asymptotically like , so decreasing very slowly or even increasing.
5. Shift-Invariant Differencers and Accumulators
5.1. Causal
- It is a moving-average system, which is sometimes called a “feedforward” system;
- Its impulse response is given by:
- The transfer function is
- We can associate in series as many systems as we can in such a way that the output of the -th system is the input of the next one, n-thThe transfer function of the association is given by
- A difference/sum is the output of a system: differencer/accumulator;
- The system structure is independent of the inputs;
- If the order is not a positive integer, even if the input function has finite support, the output has infinite support; in particular, if has support , is not identically null above any real value: the support is . This is a very important fact that is frequently forgotten or dismissed.
- If the input is a right-hand function, so is the output; in particular, if then for negative t and for , we have
- The ROC of the transfer function is defined by , as expected, since we are dealing with a causal system.
5.2. Anti-Causal
- It is also a moving-average system;
- The LT gives
- The transfer function is
- The association in a series of n systems as above has a transfer function given by
- In a similar way, the delta accumulator is
- If the order is not a positive integer, even if the input function has finite support, the output has infinite support; in particular, if has support , is not identically null below any real value; the support is
- If the input is a left-hand function, so is the output; in particular, if then for positive t and for , we have
- The ROC of the transfer function is defined by , as expected, since we are dealing with an anti-causal system.
- We can account for the sign we removed above by inserting the factor into (57).
5.3. Properties
- Additivity and commutativity of the orders
- Neutral elementThis comes from the last property by putting , . This is very important because it states the existence of the inverse, which is in coherence with the previous sub-sections.
- Inverse elementFrom the last result, we conclude that there is always an inverse element: for every -order difference, there is always a -order difference given by the same formula.
- Associativity of the ordersIt is a consequence of the additivity.
- Derivative of the productThe delta case is slightly different as expected
5.4. Discrete-Time Differences
- Both responses have finite duration if , and the systems are called FIRs (finite impulse systems) [14].
- If , both responses extend to infinite, and the corresponding systems are IIR (infinite impulse response).
- If then for negative k, and for , we have
- Similarly, if then for positive k and we obtain for
- It is a simple task to obtain formulae for functions with other supports.
- The Z transforms of the above discrete-time differences can be obtained from the corresponding LT by setting For example, the Z transform of the nabla difference (61) is
- If, in any particular application, a time sequence with the form is used, we can make a substitution for .
5.5. Two-Sided Differences
- Riesz-type difference,
- Feller-type difference,
- Two-sided discrete Hilbert transform,With , we obtain the usual discrete-time formulation of the Hilbert transform [14].
5.6. The Tempered Differences
- Nabla TDthat has LTfor any
- Delta TDIts LT is valid for any and given byAs above, we removed a (−) sign.
- Two-sided TD
5.7. Bilinear Differences
6. Scale-Invariant Differences
- Its impulse response is given by:
- The transfer function is
- As in the shift-invariant case, if associated in series n systems, the resulting system defines the n-th order stretching difference that has a transfer function given by
7. The ARMA-Type Difference Linear Systems
8. Which Difference?
9. Discussion
Funding
Conflicts of Interest
References
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Ortigueira, M.D. Discrete-Time Fractional Difference Calculus: Origins, Evolutions, and New Formalisms. Fractal Fract. 2023, 7, 502. https://doi.org/10.3390/fractalfract7070502
Ortigueira MD. Discrete-Time Fractional Difference Calculus: Origins, Evolutions, and New Formalisms. Fractal and Fractional. 2023; 7(7):502. https://doi.org/10.3390/fractalfract7070502
Chicago/Turabian StyleOrtigueira, Manuel Duarte. 2023. "Discrete-Time Fractional Difference Calculus: Origins, Evolutions, and New Formalisms" Fractal and Fractional 7, no. 7: 502. https://doi.org/10.3390/fractalfract7070502