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An analog computer is a form of computer using electronic or mechanical phenomena to model the problem being solved by using one kind of physical quantity to represent another.
The term is used in distinction to digital computers, in which physical or mechanical phenomena are used to construct a finite-state machine which is then used to model the problem being solved. There is an intermediate group, hybrid computers, in which a digital computer is used to control and organize inputs and outputs to and from attached analogue devices; for instance analogue devices might be used to help generate initial values for iterations, or the analog computer might be used to solve a non-analytic differential equation problem.
Some examples:
Computations are often performed, in analog computers, by using properties of electrical resistance, voltages and so on. For example, a simple two variable adder can be created by two current sources in parallel. The first value is set by adjusting the first current source (to say x milliamperes), and the second value is set by adjusting the second current source (say y milliamps). Measuring the current across the two at their junction to signal ground will give the sum as a current resistance x+y milliamps. Other calculations are performed similarly, using operational amplifiers and other circuits for other tasks.
The use of electrical properties in analog computers means that certain calculations on a computer are performed in real time, without calculation delays as on digital computers. This property allows certain useful calculations that are comparatively "difficult" for digital computers to perform - for example numerical integration. These computers can integrate - essentially calculating the sum of a voltage waveform, usually by means of a capacitor which accumulates charge over time.
Nonlinear functions and calculations can be constructed to a given amount of accuracy by means of creating a diode function generator: a set of diodes and resistors of varying values. As voltage increases, the total resistance summed thus changes as the diodes successively permit current to flow.
Analog computers often have a lot of complicated framework, but they have, at their core, a set of key electrical components which perform the calculations, which the operator manipulates through the computer's framework.
The core mathematical operations used in an electric analog computer are:
In general, analog computers are limited by real, non-ideal effects. An analog signal is composed of four basic components: DC and AC magnitudes, frequency, and phase. The real limits of range on these characteristics limit analog computers. Some of these limits include the noise floor, parasitics devices within semiconductors, and the finite charge of an electron. Incidentally, for commercially available electronic components, range of these aspects of input and output signals are always figures of merit.
Analog computers, however, have been replaced by digital computers for almost all calculations. It may be stretching a point to regard some physical simulations such as wind tunnels as analog computers, because the data so obtained must then also be scaled, for example, for Reynolds number and Mach number. There is a point of view in physics based on information processing which attempts to map the physical processes to computations. Thus, from these points of view, the wind tunnel data gathering is either an experiment or a computation.
These are examples of analog computers that have been constructed or practically used:
Analog synthesizers can also be viewed as a form of analog computer, and their technology was originally based on electronic analog computer technology.
Computer theorists often refer to idealised analog computers as real computers (so called because they operate on the set of real numbers).
These idealised computers can in theory enable solve problems that are inextricable on digital computers, however, as mentioned, in reality, analog computers are far from attaining this ideal, because of noise minimization problems.
However, there is another ideal: exploiting the inherent nonlinearity of the analog computers to produce computation of power between that of digital and the former-mentioned ideal. See also super-Turing computation.
Furthermore, many analog computers are in common use in applications such as earthquake prediction, as they outperform digital computing techniques.
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