The document introduces the Genuino 101 board and its features. It contains a Curie module with a 32-bit dual core processor running at 32MHz that supports machine learning libraries. It also has a Pattern Matching Engine (PME) that allows for pattern recognition using k-nearest neighbors and Radial Basis Function classification algorithms. The document provides instructions on how to program the board using the Arduino IDE and links to additional resources like a GitHub project page.

1. Genuino 101
Presented by:
Federico Mascoma

2. Introduction

3. Introduction
Genuino 101

20. Curie
• Low Power Module
• 32 bit dual core with CK = 32Mhz
• Support MachineLearning Library
• Contains Real-Time Operating Systems (RTOS)

21. How to program the board?
Install the IDE from:
https://www.arduino.cc/en/Main/Software

22. How to program the board?
Open the IDE and
Select Arduino/Genuino 101

23. How to program the board?
Let IDE to help you!

24. PME
• The Pattern Matching Engine (PME) is a parallel data recognition
engine
• Two Classification Functions:
• k-nearest neighbors (KNN)
• Radial Basis Function (RBF)
• Classification states:
• ID - Identified , UNC - Uncertain , UNK - Unknown
• #include "CuriePME.h” is the Library that provide its API

25. Project
https://github.com/Mascoma95/Genuino101

26. Takes a pattern ”vector” of size ”vectorNumBytes”, and commits it to the
network as training data.
The ”letter-upperStart” parameter indicates to the PME which category
this training vector belongs to.
If a future input has a sufficiently similar pattern, it will be classified as
the same category passed with this pattern.

27. Takes a pattern ”vector” of
size ”vectorNumBytes”, and uses the
committed neurons in the network to
classify the pattern
Parameters
vector is a pointer to the data to be
classified. Pattern data must be no
longer than 128 bytes
vectorNumBytes is the size of the data
to be classified

28. Thanks