Hoc (programming language) and Models of neural computation

Shortcuts: Differences, Similarities, Jaccard Similarity Coefficient, References.

Difference between Hoc (programming language) and Models of neural computation

Hoc (programming language) vs. Models of neural computation

hoc, an acronym for High Order Calculator, is an interpreted programming language that was used in the 1984 book The Unix Programming Environment to demonstrate how to build interpreters using Yacc. Models of neural computation are attempts to elucidate, in an abstract and mathematical fashion, the core principles that underlie information processing in biological nervous systems, or functional components thereof.

Similarities between Hoc (programming language) and Models of neural computation

Hoc (programming language) and Models of neural computation have 1 thing in common (in Unionpedia): Neuron (software).

Neuron (software)

Neuron is a simulation environment for modeling individual and networks of neurons.

Hoc (programming language) and Neuron (software) · Models of neural computation and Neuron (software) · See more »

The list above answers the following questions

What Hoc (programming language) and Models of neural computation have in common
What are the similarities between Hoc (programming language) and Models of neural computation

Hoc (programming language) and Models of neural computation Comparison

Hoc (programming language) has 15 relations, while Models of neural computation has 68. As they have in common 1, the Jaccard index is 1.20% = 1 / (15 + 68).

References

This article shows the relationship between Hoc (programming language) and Models of neural computation. To access each article from which the information was extracted, please visit:

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