State machines are useful tools for designing electronic circuits that can perform different actions based on their current state and external inputs. However, not all inputs and outputs are ...

The output of the propagation function passes to an activation ... to deal with tens of thousands of past inputs. Another kind of deep learning algorithm—not a deep neural network—is the ...

This type of learning algorithm analyzes the input-output pairs to create a mapping function that relates inputs to outputs. The mapping function enables the model to accurately predict outputs for ...

model or simulation can be used to score software components based on their inputs, outputs, and interactions. Here are some examples of fitness functions in software design: Genetic algorithms: A ...

we provide a new algorithm to find appropriate local coordinates, in which the resulting system takes a desired target form that is state-affine, up to output and input injection. Once in the target ...

This is processed and the outcome is outputted or moved to secondary storage. In some languages the input and output is combined to form a single statement. For example, in the Python 3 code below ...

Abstract: In this article, the parameter identification problem of finite impulse response (FIR) systems with quantized inputs and binary outputs is studied when ... input and designs different ...

Recall that a function can be thought of as a machine which takes an input in (say x) and then depending on what that input is, it returns an output (say y) by some predefined rule (say f). The graph ...

It processes inputs, such as numbers or data, to produce outputs, such as results or solutions. Algorithms are essential to processing data and executing functions in computer science, mathematics, ...