Latest AI/Neural Networks Technical Articles

Electromagnetic-based side-channel attacks are non-invasive, meaning the attacker does not need physical access to the…

Electromagnetic-based side-channel attacks are non-invasive, meaning the attacker does not need physical access to the device to steal information. We’ll look at how these EM side-channel attacks work.

Indispensable for modern electrical engineering, application-specific integrated circuits (ASICs) form a diverse group of…

Indispensable for modern electrical engineering, application-specific integrated circuits (ASICs) form a diverse group of integrated circuits (ICs) that help designers to optimize sophisticated electronic devices.

We’ll be walking you through creating a robotic subsystem with a voice-activated motor leveraging machine learning (ML)…

We’ll be walking you through creating a robotic subsystem with a voice-activated motor leveraging machine learning (ML) and an Arduino Nano 33 BLE Sense.

This article is a primer into the basics of RISC-V. The open architecture philosophy is exposed, along with a technical…

This article is a primer into the basics of RISC-V. The open architecture philosophy is exposed, along with a technical description of the modular ISA, and some commercial RISC-V microprocessor implementations.

This article aims to contextualize machine learning (ML) for hardware and embedded engineers, what it is, how it works,…

This article aims to contextualize machine learning (ML) for hardware and embedded engineers, what it is, how it works, why it matters, and how TinyML fits in.

Learn the basics of side channel attacks (SCAs), the threat they pose security for hardware-level security, and why they…

Learn the basics of side channel attacks (SCAs), the threat they pose security for hardware-level security, and why they can be so powerful.

This article will give a foundational understanding of quantization in the context of machine learning, specifically tiny…

This article will give a foundational understanding of quantization in the context of machine learning, specifically tiny machine learning (tinyML).

Learn about a subsection of machine learning (ML) called Tiny Machine Learning (TinyML), what it is, its applications,…

Learn about a subsection of machine learning (ML) called Tiny Machine Learning (TinyML), what it is, its applications, hardware and software requirements, and its benefits.

In this article, we’ll take a deeper look at how PUFs are classified, the attributes that make a “good” PUF, and…

In this article, we’ll take a deeper look at how PUFs are classified, the attributes that make a “good” PUF, and design tradeoffs.

Learn the key parts of an autoencoder, how a variational autoencoder improves on it, and how to build and train a…

Learn the key parts of an autoencoder, how a variational autoencoder improves on it, and how to build and train a variational autoencoder using TensorFlow.

This article discusses a complication that can prevent your Perceptron from achieving adequate classification accuracy.

This article discusses a complication that can prevent your Perceptron from achieving adequate classification accuracy.

This article shows you how to add bias values to a multilayer Perceptron implemented in a high-level programming language…

This article shows you how to add bias values to a multilayer Perceptron implemented in a high-level programming language such as Python.

In this article, we’ll perform some classification experiments and gather data on the relationship between hidden-layer…

In this article, we’ll perform some classification experiments and gather data on the relationship between hidden-layer dimensionality and network performance.

This article provides guidelines for configuring the hidden portion of a multilayer Perceptron.

This article provides guidelines for configuring the hidden portion of a multilayer Perceptron.

In this article, we’ll use Excel-generated samples to train a multilayer Perceptron, and then we’ll see how the…

In this article, we’ll use Excel-generated samples to train a multilayer Perceptron, and then we’ll see how the network performs with validation samples.

This article explains why validation is particularly important when we’re processing data using a neural network.

This article explains why validation is particularly important when we’re processing data using a neural network.

This article takes you step by step through a Python program that will allow us to train a neural network and perform…

This article takes you step by step through a Python program that will allow us to train a neural network and perform advanced classification.

This article discusses the Perceptron configuration that we will use for our experiments with neural-network training and…

This article discusses the Perceptron configuration that we will use for our experiments with neural-network training and classification, and we’ll also look at the related topic of bias nodes.

This article presents the equations that we use when performing weight-update computations, and we’ll also discuss the…

This article presents the equations that we use when performing weight-update computations, and we’ll also discuss the concept of backpropagation.