看到一句话，有理

本视频为陈吕洲在第六届全国高等学校计算机硬件课程教学论坛上的报告。
介绍当今全球流行的硬件开发平台（Arduino、mbed、linux等）及硬件厂家支持策略（ARM、intel等），探讨硬件开发平台对当今硬件开发工作的影响及国内外高等院校嵌入式教育模式的变革。

陈吕洲
成都墨之坊科技有限公司CEO，Arduino中文社区（arduino.cn）创始人

视频：https://www.bilibili.com/video/av10809442/

重新设计了网站的logo

#include "CurieIMU.h"
#include "CuriePME.h"

const unsigned int buttonPin = 4;
const unsigned int trainingReps = 4;
const unsigned int classification = 3;
const unsigned int len = 128;

void training()
{
    unsigned int currentClassification = 0;
    while ( currentClassification < classification ) {
        currentClassification++;

        unsigned int currentTraining = 0;
        while( currentTraining < trainingReps ) {
            currentTraining++;
            // 获取传感器数据
            byte data[128] = readVectorFromIMU(vector);
            // 使用该数据进行训练
            CuriePME.learn(vector, 128, currentClassification);
        }






    }

    unsigned int currentTraining = 0;
    while (i < repeat) {
        byte vector[vectorNumBytes];

        if (i) Serial.println("And again...");

        readVectorFromIMU(vector);
        CuriePME.learn(vector, vectorNumBytes, letter - upperStart);

        Serial.println("Got it!");
        delay(1000);
        ++i;
    }
}


/* Sample rate for accelerometer */
const unsigned int sampleRateHZ = 200;

/* No. of bytes that one neuron can hold */
const unsigned int vectorNumBytes = 128;

/* Number of processed samples (1 sample == accel x, y, z)
 * that can fit inside a neuron */
const unsigned int samplesPerVector = (vectorNumBytes / 3);


const unsigned int sensorBufSize = 2048;
const int IMULow = -32768;
const int IMUHigh = 32767;

void setup()
{
    Serial.begin(9600);
    while(!Serial);
    pinMode(buttonPin, INPUT);
    CurieIMU.begin();
    CuriePME.begin();
    CurieIMU.setAccelerometerRate(sampleRateHZ);
    CurieIMU.setAccelerometerRange(2);
    // 进入训练状态
    trainLetters();
    Serial.println("Training complete. Now, draw some letters (remember to ");
    Serial.println("hold the button) and see if the PME can classify them.");
}

void loop ()
{
    // 进入识别状态
    byte vector[vectorNumBytes];
    unsigned int category;
    char letter;

    /* Record IMU data while button is being held, and
     * convert it to a suitable vector */
    readVectorFromIMU(vector);

    /* Use the PME to classify the vector, i.e. return a category
     * from 1-26, representing a letter from A-Z */
    category = CuriePME.classify(vector, vectorNumBytes);

    if (category == CuriePME.noMatch) {
        Serial.println("Don't recognise that one-- try again.");
    } else {
        letter = category + upperStart;
        Serial.println(letter);
    }
}

/* Simple "moving average" filter, removes low noise and other small
 * anomalies, with the effect of smoothing out the data stream. */
byte getAverageSample(byte samples[], unsigned int num, unsigned int pos,
                   unsigned int step)
{
    unsigned int ret;
    unsigned int size = step * 2;

    if (pos < (step * 3) || pos > (num * 3) - (step * 3)) {
        ret = samples[pos];
    } else {
        ret = 0;
        pos -= (step * 3);
        for (unsigned int i = 0; i < size; ++i) {
            ret += samples[pos - (3 * i)];
        }

        ret /= size;
    }

    return (byte)ret;
}

/* We need to compress the stream of raw accelerometer data into 128 bytes, so
 * it will fit into a neuron, while preserving as much of the original pattern
 * as possible. Assuming there will typically be 1-2 seconds worth of
 * accelerometer data at 200Hz, we will need to throw away over 90% of it to
 * meet that goal!
 *
 * This is done in 2 ways:
 *
 * 1. Each sample consists of 3 signed 16-bit values (one each for X, Y and Z).
 *    Map each 16 bit value to a range of 0-255 and pack it into a byte,
 *    cutting sample size in half.
 *
 * 2. Undersample. If we are sampling at 200Hz and the button is held for 1.2
 *    seconds, then we'll have ~240 samples. Since we know now that each
 *    sample, once compressed, will occupy 3 of our neuron's 128 bytes
 *    (see #1), then we know we can only fit 42 of those 240 samples into a
 *    single neuron (128 / 3 = 42.666). So if we take (for example) every 5th
 *    sample until we have 42, then we should cover most of the sample window
 *    and have some semblance of the original pattern. */
void undersample(byte samples[], int numSamples, byte vector[])
{
    unsigned int vi = 0;
    unsigned int si = 0;
    unsigned int step = numSamples / samplesPerVector;
    unsigned int remainder = numSamples - (step * samplesPerVector);

    /* Centre sample window */
    samples += (remainder / 2) * 3;
    for (unsigned int i = 0; i < samplesPerVector; ++i) {
        for (unsigned int j = 0; j < 3; ++j) {
            vector[vi + j] = getAverageSample(samples, numSamples, si + j, step);
        }

        si += (step * 3);
        vi += 3;
    }
}

void readVectorFromIMU(byte vector[])
{
    byte accel[sensorBufSize];
    int raw[3];

    unsigned int samples = 0;
    unsigned int i = 0;

    /* Wait until button is pressed */
    while (digitalRead(buttonPin) == LOW);

    /* While button is being held... */
    while (digitalRead(buttonPin) == HIGH) {
        if (CurieIMU.accelDataReady()) {

            CurieIMU.readAccelerometer(raw[0], raw[1], raw[2]);
            accel[i] = (byte) map(raw[0], IMULow, IMUHigh, 0, 255);
            accel[i + 1] = (byte) map(raw[1], IMULow, IMUHigh, 0, 255);
            accel[i + 2] = (byte) map(raw[2], IMULow, IMUHigh, 0, 255);
            i += 3;
            ++samples;
            /* If there's not enough room left in the buffers
            * for the next read, then we're done */
            if (i + 3 > sensorBufSize) {
                break;
            }
        }
    }

    undersample(accel, samples, vector);
}

void trainLetter(char letter, unsigned int repeat)
{
    unsigned int i = 0;

    while (i < repeat) {
        byte vector[vectorNumBytes];

        if (i) Serial.println("And again...");

        readVectorFromIMU(vector);
        CuriePME.learn(vector, vectorNumBytes, letter - upperStart);

        Serial.println("Got it!");
        delay(1000);
        ++i;
    }
}

void trainLetters()
{
    for (char i = trainingStart; i <= trainingEnd; ++i) {
        Serial.print("Hold down the button and draw the letter '");
        Serial.print(String(i) + "' in the air. Release the button as soon ");
        Serial.println("as you are done.");

        trainLetter(i, trainingReps);
        Serial.println("OK, finished with this letter.");
        delay(2000);
    }
}