Programming and Language
Aunt Bette's Homemade Pecan Pie |
Rockin’ Rocky Road Ice Cream |
Tom’s Heavenly Apple Strudel |
Joe’s Divine Butter Tarts |
Aunt Bette's Homemade Pecan Pie |
Rockin’ Rocky Road Ice Cream |
Tom’s Heavenly Apple Strudel |
Joe’s Divine Butter Tarts |
Aunt Bette's Homemade Pecan Pie |
Rockin’ Rocky Road Ice Cream |
Tom’s Heavenly Apple Strudel |
Joe’s Divine Butter Tarts |
Aunt Bette's Homemade Pecan Pie |
Rockin’ Rocky Road Ice Cream |
Tom’s Heavenly Apple Strudel |
Joe’s Divine Butter Tarts |
Schindler Automates Physical Model Verification Framework Using Simulink Test
Jan 2020
Schindler developed an automated test framework called Models’ Automated Test Harnesses (MATHS) using Simulink Test™ to perform system-level and model-in-theloop (MIL) tests for subsystem components. With Simulink Test, Schindler engineers can create test harnesses and write corresponding test cases.
IDNEO Develops AUTOSAR Components Using Agile Model-Based Design
Jan 2020
IDNEO has been using Model-Based Design for four years, which has led to significant business improvements. When their customers also use Simulink®, ambiguities in requirements are avoided and development time can be cut in half.
What Is int8 Quantization and Why Is It Popular for Deep Neural Networks?
Oct 2019
By Ram Cherukuri, MathWorks
int8 quantization has become a popular approach for such optimizations not only for machine learning frameworks like TensorFlow and PyTorch but also for hardware toolchains like NVIDIA® TensorRT and Xilinx® DNNDK—mainly because int8 uses 8-bit integers instead of floating-point numbers and integer math instead of floating-point math, reducing both memory and computing requirements.
Third-Party Products: Solutions for Developing Wireless Systems with MATLAB and Simulink
Oct 2019
By Mathworks Staff
Wireless hardware platforms integrated with MATLAB® and Simulink® enable engineers, hobbyists, and students to move from theory to prototyping designs and deploying production systems.
Reinforcement Learning: A Brief Guide
Sep 219
By Emmanouil Tzorakoleftherakis, MathWorks
Reinforcement learning has the potential to solve tough decision-making problems in many applications, including industrial automation, autonomous driving, video game playing, and robotics.
Predictive Maintenance Using a Digital Twin
May 2019
By Steve Miller, MathWorks
When industrial equipment breaks, the resulting problem often is not the cost of replacing that equipment but the forced downtime. A production line standing still may mean thousands of dollars lost every minute. Performing regular maintenance can help avoid unplanned downtime, but it does not guarantee that equipment will not fail.
Modeling and Simulating Battery Performance for Design Optimization
Feb 2019
By Cecilia Wang, Romeo Power
Reinforcement learning has the potential to solve tough decision-making problems in many applications, including industrial automation, autonomous driving, video game playing, and robotics.