Robust Reservoir Generation by Correlation-Based Learning (Yamazaki & Tanaka 2008)

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Accession:116806
"Reservoir computing (RC) is a new framework for neural computation. A reservoir is usually a recurrent neural network with fixed random connections. In this article, we propose an RC model in which the connections in the reservoir are modifiable. ... We apply our RC model to trace eyeblink conditioning. The reservoir bridged the gap of an interstimulus interval between the conditioned and unconditioned stimuli, and a readout neuron was able to learn and express the timed conditioned response."
Reference:
1 . Yamazaki T, Tanaka S (2009) Robust Reservoir Generation by Correlation-Based Learning Advances in Artificial Neural Systems 2009:1-7
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism:
Cell Type(s):
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: C or C++ program;
Model Concept(s): Temporal Pattern Generation; Spatio-temporal Activity Patterns; Rate-coding model neurons; Learning;
Implementer(s):
/* 
   A C-program for MT19937, with initialization improved 2002/2/10.
   Coded by Takuji Nishimura and Makoto Matsumoto.
   This is a faster version by taking Shawn Cokus's optimization,
   Matthe Bellew's simplification, Isaku Wada's real version.

   Before using, initialize the state by using init_genrand(seed) 
   or init_by_array(init_key, key_length).

   Copyright (C) 1997 - 2002, Makoto Matsumoto and Takuji Nishimura,
   All rights reserved.                          

   Redistribution and use in source and binary forms, with or without
   modification, are permitted provided that the following conditions
   are met:

     1. Redistributions of source code must retain the above copyright
        notice, this list of conditions and the following disclaimer.

     2. Redistributions in binary form must reproduce the above copyright
        notice, this list of conditions and the following disclaimer in the
        documentation and/or other materials provided with the distribution.

     3. The names of its contributors may not be used to endorse or promote 
        products derived from this software without specific prior written 
        permission.

   THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
   "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
   LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
   A PARTICULAR PURPOSE ARE DISCLAIMED.  IN NO EVENT SHALL THE COPYRIGHT OWNER OR
   CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
   EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
   PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
   PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
   LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
   NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
   SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.


   Any feedback is very welcome.
   http://www.math.keio.ac.jp/matumoto/emt.html
   email: matumoto@math.keio.ac.jp
*/

#include <stdio.h>

/* Period parameters */  
#define N 624
#define M 397
#define MATRIX_A 0x9908b0dfUL   /* constant vector a */
#define UMASK 0x80000000UL /* most significant w-r bits */
#define LMASK 0x7fffffffUL /* least significant r bits */
#define MIXBITS(u,v) ( ((u) & UMASK) | ((v) & LMASK) )
#define TWIST(u,v) ((MIXBITS(u,v) >> 1) ^ ((v)&1UL ? MATRIX_A : 0UL))

static unsigned long state[N]; /* the array for the state vector  */
static int left = 1;
static int initf = 0;
static unsigned long *next;

/* initializes state[N] with a seed */
void init_genrand(unsigned long s)
{
    int j;
    state[0]= s & 0xffffffffUL;
    for (j=1; j<N; j++) {
        state[j] = (1812433253UL * (state[j-1] ^ (state[j-1] >> 30)) + j); 
        /* See Knuth TAOCP Vol2. 3rd Ed. P.106 for multiplier. */
        /* In the previous versions, MSBs of the seed affect   */
        /* only MSBs of the array state[].                        */
        /* 2002/01/09 modified by Makoto Matsumoto             */
        state[j] &= 0xffffffffUL;  /* for >32 bit machines */
    }
    left = 1; initf = 1;
}

/* initialize by an array with array-length */
/* init_key is the array for initializing keys */
/* key_length is its length */
void init_by_array(init_key, key_length)
unsigned long init_key[], key_length;
{
    int i, j, k;
    init_genrand(19650218UL);
    i=1; j=0;
    k = (N>key_length ? N : key_length);
    for (; k; k--) {
        state[i] = (state[i] ^ ((state[i-1] ^ (state[i-1] >> 30)) * 1664525UL))
          + init_key[j] + j; /* non linear */
        state[i] &= 0xffffffffUL; /* for WORDSIZE > 32 machines */
        i++; j++;
        if (i>=N) { state[0] = state[N-1]; i=1; }
        if (j>=key_length) j=0;
    }
    for (k=N-1; k; k--) {
        state[i] = (state[i] ^ ((state[i-1] ^ (state[i-1] >> 30)) * 1566083941UL))
          - i; /* non linear */
        state[i] &= 0xffffffffUL; /* for WORDSIZE > 32 machines */
        i++;
        if (i>=N) { state[0] = state[N-1]; i=1; }
    }

    state[0] = 0x80000000UL; /* MSB is 1; assuring non-zero initial array */ 
    left = 1; initf = 1;
}

static void next_state(void)
{
    unsigned long *p=state;
    int j;

    /* if init_genrand() has not been called, */
    /* a default initial seed is used         */
    if (initf==0) init_genrand(5489UL);

    left = N;
    next = state;
    
    for (j=N-M+1; --j; p++) 
        *p = p[M] ^ TWIST(p[0], p[1]);

    for (j=M; --j; p++) 
        *p = p[M-N] ^ TWIST(p[0], p[1]);

    *p = p[M-N] ^ TWIST(p[0], state[0]);
}

/* generates a random number on [0,0xffffffff]-interval */
unsigned long genrand_int32(void)
{
    unsigned long y;

    if (--left == 0) next_state();
    y = *next++;

    /* Tempering */
    y ^= (y >> 11);
    y ^= (y << 7) & 0x9d2c5680UL;
    y ^= (y << 15) & 0xefc60000UL;
    y ^= (y >> 18);

    return y;
}

/* generates a random number on [0,0x7fffffff]-interval */
long genrand_int31(void)
{
    unsigned long y;

    if (--left == 0) next_state();
    y = *next++;

    /* Tempering */
    y ^= (y >> 11);
    y ^= (y << 7) & 0x9d2c5680UL;
    y ^= (y << 15) & 0xefc60000UL;
    y ^= (y >> 18);

    return (long)(y>>1);
}

/* generates a random number on [0,1]-real-interval */
double genrand_real1(void)
{
    unsigned long y;

    if (--left == 0) next_state();
    y = *next++;

    /* Tempering */
    y ^= (y >> 11);
    y ^= (y << 7) & 0x9d2c5680UL;
    y ^= (y << 15) & 0xefc60000UL;
    y ^= (y >> 18);

    return (double)y * (1.0/4294967295.0); 
    /* divided by 2^32-1 */ 
}

/* generates a random number on [0,1)-real-interval */
double genrand_real2(void)
{
    unsigned long y;

    if (--left == 0) next_state();
    y = *next++;

    /* Tempering */
    y ^= (y >> 11);
    y ^= (y << 7) & 0x9d2c5680UL;
    y ^= (y << 15) & 0xefc60000UL;
    y ^= (y >> 18);

    return (double)y * (1.0/4294967296.0); 
    /* divided by 2^32 */
}

/* generates a random number on (0,1)-real-interval */
double genrand_real3(void)
{
    unsigned long y;

    if (--left == 0) next_state();
    y = *next++;

    /* Tempering */
    y ^= (y >> 11);
    y ^= (y << 7) & 0x9d2c5680UL;
    y ^= (y << 15) & 0xefc60000UL;
    y ^= (y >> 18);

    return ((double)y + 0.5) * (1.0/4294967296.0); 
    /* divided by 2^32 */
}

/* generates a random number on [0,1) with 53-bit resolution*/
double genrand_res53(void) 
{ 
    unsigned long a=genrand_int32()>>5, b=genrand_int32()>>6; 
    return(a*67108864.0+b)*(1.0/9007199254740992.0); 
} 
/* These real versions are due to Isaku Wada, 2002/01/09 added */

// int main(void)
// {
//     int i;
//     unsigned long init[4]={0x123, 0x234, 0x345, 0x456}, length=4;
//     init_by_array(init, length);
//     /* This is an example of initializing by an array.       */
//     /* You may use init_genrand(seed) with any 32bit integer */
//     /* as a seed for a simpler initialization                */
//     printf("1000 outputs of genrand_int32()\n");
//     for (i=0; i<1000; i++) {
//       printf("%10lu ", genrand_int32());
//       if (i%5==4) printf("\n");
//     }
//     printf("\n1000 outputs of genrand_real2()\n");
//     for (i=0; i<1000; i++) {
//       printf("%10.8f ", genrand_real2());
//       if (i%5==4) printf("\n");
//     }
// 
//     return 0;
// }

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