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An instruction set simulator (ISS) is a simulation model, usually coded in a high-level programming language, which mimics the behavior of a mainframe or microprocessor by "reading" instructions and maintaining internal variables which represent the processor's registers.
Since simulation can accommodate complex problems of this sort, it is often used in analysing real options [1] where management's decision at any point is a function of multiple underlying variables. Simulation can similarly be used to value options where the payoff depends on the value of multiple underlying assets [ 8 ] such as a Basket ...
"A function φ is primitive recursive in ψ 1, ..., ψ k (briefly Ψ), if there is a finite sequence φ 1, ..., φ k of (occurrences of) functions ... such that each function of the sequence is either one of the functions Ψ (the assumed functions), or an initial function, or an immediate dependent of preceding functions, and the last function ...
For example, elements can use real or integer values to simulate DSP functions or sampled data filters. Because the event-driven algorithm is faster than the standard SPICE matrix solution, simulation time is greatly reduced for circuits that use event-driven models in place of analog models. [5]
The first applications of computer simulations for dynamic systems was in the aerospace industry. [5] Commercial uses of dynamic simulation are many and range from nuclear power, steam turbines, 6 degrees of freedom vehicle modeling, electric motors, econometric models, biological systems, robot arms, mass-spring-damper systems, hydraulic systems, and drug dose migration through the human body ...
One particular motivating example is the use of commitment schemes in zero-knowledge proofs.Commitments are used in zero-knowledge proofs for two main purposes: first, to allow the prover to participate in "cut and choose" proofs where the verifier will be presented with a choice of what to learn, and the prover will reveal only what corresponds to the verifier's choice.
Clearly, this means that n must have the value zero, and so a contradiction arises if one can show that in fact n is not zero. In many transcendence proofs, proving that n ≠ 0 is very difficult, and hence a lot of work has been done to develop methods that can be used to prove the non-vanishing of certain expressions.
In computer science, an operation, function or expression is said to have a side effect if it has any observable effect other than its primary effect of reading the value of its arguments and returning a value to the invoker of the operation.