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This Is How To Make Artificial Neuron Models in C++

This Is How To Make Artificial Neuron Models in C++

What is a simple artificial neuron in C++? How can we code a simple AI neuron in C++? Should we use arrays, classes, or structs? In previous AI Tech posts, we answered all these questions. In this post, we will list all the simple AI models in C++. There can be many models depending on your research. We have tried to keep these posts simple to understand the different ways of AI programming in C++ with the use of  C++ IDE.

What is an Artificial Neural Network or ANN?

An Artificial Neural Network, also called ANN is a part of Artificial Intelligence that models artificial neurons connected in artificial layers. C++ allows us to create our own AI neuron models. A Minimum Artificial Neuron has an activation value (a), an activation function ( phi() ) and weighted (w) input net links. So it has one activation value, one activation function and one or more weights depends on number of its input nets.

We prepared a very simple Artificial Neural Network example with an Activation Function.

This image has an empty alt attribute; its file name is SimpleANN2-1024x576.png

By the given example above, Here we go,

Is there a simple Artificial Neuron Model example in C++?

In the introduction post of the AI Tech series, we gave a very Simple Artificial Neural Network Example with a Simple Artificial Neuron in C++ as below,

Now, let’s do this same example with different neuron models in C++;

Is there an array-based Artificial Neuron Model example in C++?

Yes. Here is another simple neuron example with arrays. This example is also good for C applications on IoT devices. If you have a constant network and you know the trained data values, this model may be easy to check activation of neurons. Arrays allow you to use for loops.

Is there a structure-based Artificial Neuron Model example for the C language?

This example is perfect for calculating high numbers of neurons on machines which code can be compiled only in C:

We can also add a ‘fire’ function to fire each neurons something like this;

Is there a Class-Based Artificial Neuron Model Example in C++?

Classes are the best to use in C++; they are safe and much more functional. If you are new to Classes please read our previous posts about Classes & Objects.

If you are developing an AI algorithm for the C based devices, IoTs, and so on, then simple model, array-based models – but mostly struct-based AI models can be useful. These can also be useful with C++ based devices. If you are developing modern applications on Windows, macOS, iOS, Android or Linux then Struct- and Class-based models can be used. Class-based models can be also used on some IoTs which has C++ supports.

These example models above are very simple artificial neuron models. In C++ we’re lucky in that we can create our own models by using C++’s strong Classes, Objects and Structure features.


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About author

Dr. Yilmaz Yoru has 35+ years of coding with more than 30+ programming languages, mostly C++ on Windows, Android, Mac-OS, iOS, Linux, and some other operating systems. He was born in 1974, Eskisehir-Turkey, started coding in college and graduated from the department of Mechanical Engineering of Eskisehir Osmangazi University in 1997. He worked as a research assistant at the same university for more than 10 years. He received his MSc and PhD degrees from the same department at the same university. Since 2012, he is the founder and CEO of Esenja LLC Company. He has married and he is a father of a son. Some of his interests are Programming, Thermodynamics, Fluid Mechanics, Artificial Intelligence, 2D & 3D Designs, and high-end innovations.
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