491:) deterministic systems. Unfortunately, in the case of analog systems, none of these properties are ever perfectly achieved. Linearity implies that operation of a system can be scaled to arbitrarily large magnitudes, which is not possible. By definition of time-invariance, it is violated by aging effects that can change the outputs of analog systems over time (usually years or even decades).
440:. The difference can be explained by considering the meaning of memory in a system. Future output of a system with memory depends on future input and a number of state variables, such as values of the input or output at various times in the past. If the number of state variables necessary to describe future output is finite, the system is lumped; if it is infinite, the system is distributed.
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Note: It is not possible to physically realize a non-causal system operating in "real time". However, from the standpoint of analysis, they are important for two reasons. First, the ideal system for a given application is often a noncausal system, which although not physically possible can give
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It is often useful (or necessary) to break up a system into smaller pieces for analysis. Therefore, we can regard a SIMO system as multiple SISO systems (one for each output), and similarly for a MIMO system. By far, the greatest amount of work in system analysis has been with SISO systems,
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characterizes electrical systems and their properties. System analysis can be used to represent almost anything from population growth to audio speakers; electrical engineers often use it because of its direct relevance to many areas of their discipline, most notably
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insight into the design of a derived causal system to accomplish a similar purpose. Second, there are instances when a system does not operate in "real time" but is rather simulated "off-line" by a computer, such as post-processing an audio or video recording.
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and other random phenomena ensure that the operation of any analog system will have some degree of stochastic behavior. Despite these limitations, however, it is usually reasonable to assume that deviations from these ideals will be small.
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Systems with analog input and digital output or digital input and analog output are possible. However, it is usually easiest to break these systems up for analysis into their analog and digital parts, as well as the necessary
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systems do not depend on any past input. In common usage memoryless systems are also independent of future inputs. An interesting consequence of this is that the impulse response of any memoryless system is itself a scaled
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systems, for instance, are often used in integrated circuits. The methods developed for analyzing discrete time signals and systems are usually applied to digital and analog signals and systems.
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Another way to characterize systems is by whether their output at any given time depends only on the input at that time or perhaps on the input at some time in the past (or in the future!).
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Further, some non-causal systems can operate in pseudo-real time by introducing lag: if a system depends on input for 1 second in future, it can process in real time with 1 second lag.
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for digital and lumped analog LTI systems). Alternatively, we can think of an LTI system being completely specified by its
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LTI systems is important. A lumped LTI system is specified by a finite number of parameters, be it the
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of its differential equation, whereas specification of a distributed LTI system requires a complete
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This article is about the field of electrical engineering. For the interdisciplinary field, see
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Finally, systems may be characterized by certain properties which facilitate their analysis:
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in time, as well as continuous or discrete in the values they take at any given time:
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if it has the superposition and scaling properties. A system that is not linear is
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although many parts inside SISO systems have multiple inputs (such as adders).
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A system that will produce different outputs for a given input is said to be
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Signals that are continuous in time and continuous in value are known as
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Signals that are discrete in time and continuous in value are called
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Signals that are discrete in time and discrete in value are known as
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A system that has digital input and digital output is known as a
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A system that has analog input and analog output is known as an
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Oppenheim, Alan; Willsky, Alan; Nawab, S. (1996-08-06).
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Analog systems with memory may be further classified as
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A system is characterized by how it responds to input
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762:(2nd ed.). Upper Saddle River, NJ: Pearson.
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57:Learn how and when to remove these messages
409:systems do not depend on any future input.
223:Learn how and when to remove this message
205:Learn how and when to remove this message
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570:Important concepts in system analysis
561:, or partial differential equations.
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143:adding citations to reliable sources
419:systems do depend on future input.
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553:of its transfer function, or the
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674:Ordinary differential equations
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512:Linear time-invariant systems
627:Continuous Fourier transform
576:Linear time-invariant system
532:linear differential equation
506:Linear time-invariant system
382:digital-to-analog converter
259:Characterization of systems
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800:Digital signal processing
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678:Difference equations
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665:transfer functions
648:Frequency response
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466:; otherwise it is
340:Switched capacitor
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708:Limit cycle
636:Z-transform
584:theory and
547:distributed
500:LTI systems
438:distributed
401:with memory
104:August 2016
784:Categories
745:References
658:Bode plots
516:LTI system
481:stochastic
456:non-linear
413:Non-causal
393:Memoryless
306:continuous
165:newspapers
43:improve it
702:transient
693:Causality
688:Stability
49:talk page
704:behavior
683:Feedback
565:See also
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399:Systems
396:impulse.
310:discrete
604:systems
598:systems
265:signals
179:scholar
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582:Filter
578:theory
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450:linear
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407:Causal
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293:MIMO
286:MISO
280:SIMO
273:SISO
251:and
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81:list
489:LTI
436:or
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