Welcome to Intelligent Additive Manufacturing Lab

We're aiming to create a knowledge hub for 3D printing of the future.

RegisterLogin

About Us

 We hope to predict the properties of materials through theories and simulations.

This page contains various simulation and data analysis methods to help people study 3D printing.

For more detail or complicated problems discussion, please contact us.

Main Content

Fast Fourier Transform

In this method, Fast Fourier Transform and Gaussian Filter are used to determining the frequency signature generated by the detected object. As a result, a feature of motion is printed. Also, a Gaussian Filter achieves noise elimination.

Gabor Transform

Fourier transforms is a great method to determine which frequencies are present in a signal. However, it can not tell us where those frequencies occur in time. In order to extract the local information from the Fourier Transform of the signal. Gabor Transform was proposed to tell where those frequencies occur in time.

Decomposition Methods

Various decomposition methods will be introduced to solve Ax=b. It includes lower-upper (LU) decomposition, QR decomposition, and singular value decomposition (SVD). Also, some dimensionality reduction means, such as principal component analysis and linear discriminant analysis.

Dynamic Mode Decomposition

Dynamic Mode Decomposition can exploit dimensionality reduction of two video clips. DMD will compute a data set, each of which is associated with a fixed oscillation frequency and decay/growth rate. So, in a linear system, these modes and frequencies are analogous to the normal modes of the system. Generally speaking, they are approximations of the modes and eigenvalues of the composition operator. It can be used to separate a motion’s foreground and background.

Support Vector Machine (SVM)

A support vector machine (SVM) is a supervised machine learning model that uses classification algorithms for two-group classification problems. After giving an SVM model sets of labeled training data for each category, they’re able to categorize new text.

Artificial Neural Network

Artificial neural networks (ANNs) can recognize underlying relationships in a set of data through a process that mimics the way the human brain operates. In this sense, neural networks refer to systems of artificial neurons. By adapting to changing input data set, the network generates the best possible result.

Founded by Doctoral Researchers from University of Cambridge & Washington

contact@iam-lab.com

+1 (937) 9564745

©  2023 Intelligent Additive Manufacturing. All Rights Reserved