computer science

Neural Networks (journal)

Neural Networks (journal) is a computer science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Neural Networks (journal) rather than just read about it. In short: Neural Networks is a monthly peer-reviewed scientific journal and an official journal of the International Neural Network Society, European Neural Network Society, and Japanese Neural Network Society. History The journal was established in 1988 and is published by Elsevier.

Key takeaways

Neural Networks (journal) belongs to computer science; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect Neural Networks (journal) to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of Neural Networks (journal) from memory before moving on to harder problems.

Reference excerpt

Neural Networks is a monthly peer-reviewed scientific journal and an official journal of the International Neural Network Society, European Neural Network Society, and Japanese Neural Network Society.

History The journal was established in 1988 and is published by Elsevier. It covers all aspects of research on artificial neural networks. The founding editor-in-chief was Stephen Grossberg (Boston University). The current editors-in-chief are DeLiang Wang (Ohio State University) and Taro Toyoizumi (RIKEN Center for Brain Science).

Abstracting and indexing The journal is abstracted and indexed in Scopus and the Science Citation Index Expanded. According to the Journal Citation Reports, the journal has a 2022 impact factor of 7.8.

References

External links Official website

Worked examples

Example 1 — a first encounter with Neural Networks (journal)

Start with the simplest possible case. Write down what Neural Networks (journal) claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In computer science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Neural Networks (journal) before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Neural Networks (journal) ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Neural Networks (journal)

In research: Neural Networks (journal) appears in computer science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses Neural Networks (journal) in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: Neural Networks (journal) is common in secondary-school and first-year university syllabi. It links to neighbouring topics Academic journals established in 1988, Artificial intelligence journals, Artificial neural networks, so understanding it makes those chapters shorter.
In everyday life: Look for Neural Networks (journal) outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Neural Networks (journal) in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Neural Networks (journal) means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain Neural Networks (journal) out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Neural Networks (journal) in simple terms?

Why does Neural Networks (journal) matter?

Because it connects several computer science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Neural Networks (journal)?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Neural Networks (journal).