An easy, silly way to create a lookup table for an exponential decay curve - useful for ADSR envelope curves

easyExponentialDecay.cpp

#include <iomanip>
#include <iostream>

#define     EXP_TABLE_LEN       100

using namespace std;

//
// populates an array of doubles with values ranging from 1.0 to 0
// derived from an exponential decay curve
// comes in handy when you get tired of linear ADSR envelope shapes
//
void fillExpDecayTable(double table[], int arraySize)
{
    double x1 = 1.0;        // change x1 and x2 to get different result
    double x2 = 3.0;        // increase the x2 value and distance btw x1 and x2
                            // to get a curve that's more intense
    double yFloor   = x1;
    double yCeiling = x2 * x2;      // for more radical curve, set this to x2 * x2 * x2
                                    // and change line 32 to:
                                    // double yPos = ((xPos * xPos * xPos) - yFloor) / yRange;
    
    double yRange   = yCeiling - yFloor;    // you can factor all these variables
                                            // into formula
                                            // to make the program compact
    
    double xPos = x2;
    double xDelta = (x2 - x1) / arraySize;    
    
    for(int i=0; i<arraySize; i++)
    {
    	double yPos = ((xPos * xPos) - yFloor) / yRange;
    	table[i] = yPos;
    	xPos -= xDelta;
    }    
}

// let's see how the table looks
int main()
{
    double expDecayTable[EXP_TABLE_LEN];
    fillExpDecayTable(expDecayTable, EXP_TABLE_LEN);
    
    cout << "\t\t" << "expo" << "\t\t" << "linear" << endl << endl;
    cout << setprecision(2);
    
    for(int i=0; i<EXP_TABLE_LEN; i++)
    {
        cout << i << "\t\t" << expDecayTable[i] << "\t\t"
                << 1 - (double)i / EXP_TABLE_LEN << endl;
    }
    
    return 0;
}

The first image shows linear shaping using simple linear functions for the attack, decay and release stages. The second image shows exponential shaping with the table created in the program above, with the variables x1 = 1.0 and x2 = 30.0.