void matrixaddsub()
{
int i,j,m,n,cho; float a[25][25],b[25][25];
printf("Enter the dimension of Matrix as MXN");
scanf("%d %d",&m,&n);
printf("Enter the element of 1st Matrix\n");
for(i=0;i<m;i++)
{
for(j=0;j<n;j++)
{
scanf("%f",&a[i][j]);
}
}
printf("Enter the element of 2nd Matrix\n");
for(i=0;i<m;i++)
{
for(j=0;j<n;j++)
{
scanf("%f",&b[i][j]);
}
}
printf("1.Calculate Matrix Addition.\n");
printf("2.Calculate Matrix Subtraction.\n");
scanf("%d",&cho);
switch(cho)
{
case 1:
matrixadd(a,b,m,n);
break;
case 2:
matrixsub(a,b,m,n);
break;
}
}
int
accum_gauden(float32 ***denacc,
uint32 *lcl2gbl,
uint32 n_lcl2gbl,
vector_t *frame,
uint32 ***den_idx,
gauden_t *g,
int32 mean_reest,
int32 var_reest,
int32 pass2var,
float32 ***wacc,
int32 var_is_full,
FILE *pdumpfh,
float32 ***lda)
{
uint32 g_i, i, j, k, kk, l;
vector_t ***macc = g->l_macc; /* local to utt */
vector_t m;
vector_t ***mean = g->mean;
vector_t pm = NULL;
vector_t ***vacc = g->l_vacc;
vector_t v = NULL;
vector_t ****fullvacc = g->l_fullvacc;
vector_t *fv = NULL;
vector_t *cov = NULL;
vector_t dvec = NULL;
float32 ***dnom = g->l_dnom;
float32 diff;
float32 obs_cnt;
vector_t feat = NULL;
/* Apply LDA if desired. */
if (lda) {
/* Note that we ignore -ldadim here, because it's rather
* complicated to change the length of veclen for the
* output only. */
lda_transform(&frame, 1, lda, g->veclen[0], g->veclen[0]);
}
/* for each density family found in the utterance */
for (i = 0; i < n_lcl2gbl; i++) {
g_i = lcl2gbl[i];
/* for each feature */
for (j = 0; j < gauden_n_feat(g); j++) {
feat = frame[j];
if (var_is_full) {
ckd_free_2d((void **)cov);
cov = (vector_t *)ckd_calloc_2d(g->veclen[j], g->veclen[j], sizeof(float32));
ckd_free(dvec);
dvec = ckd_calloc(g->veclen[j], sizeof(float32));
}
/* for each density in the mixture density */
for (kk = 0; kk < gauden_n_top(g); kk++) {
k = den_idx[i][j][kk]; /* i.e. density k is one of the n_top densities */
obs_cnt = denacc[i][j][k]; /* observation count for density (k) at this time frame
given the model */
/* don't bother adding a bunch of
essentially zero values */
if (obs_cnt <= MIN_POS_FLOAT32)
continue;
#ifdef ACCUM_VERBOSE
printf("denacc[%u][%u][%3u] == %.3e\n", i, j, k, obs_cnt);
#endif
if (pdumpfh)
fprintf(pdumpfh, "%u %u %u %g\n", lcl2gbl[i], j, k, obs_cnt);
m = macc[i][j][k]; /* the vector accumulator for mean (i,j,k) */
if (pass2var) {
g_i = lcl2gbl[i];
pm = mean[g_i][j][k]; /* the mean (i, j, k) */
}
if (var_reest) {
if (var_is_full)
fv = fullvacc[i][j][k];
else
v = vacc[i][j][k]; /* the vector accumulator for variance (i,j,k) */
}
if (var_reest && var_is_full) {
if (!pass2var)
outerproduct(cov, feat, feat, g->veclen[j]);
else {
for (l = 0; l < g->veclen[j]; ++l)
dvec[l] = feat[l] - pm[l];
outerproduct(cov, dvec, dvec, g->veclen[j]);
}
scalarmultiply(cov, obs_cnt, g->veclen[j], g->veclen[j]);
matrixadd(fv, cov, g->veclen[j], g->veclen[j]);
}
for (l = 0; l < g->veclen[j]; l++) {
if (mean_reest) {
m[l] += obs_cnt * feat[l];
}
if (var_reest && !var_is_full) {
/* Always reest vars on untransformed features for now */
/* This does NOT work with -2passvar no (for pretty obvious reasons) */
if (!pass2var)
v[l] += obs_cnt * feat[l] * feat[l];
else {
diff = feat[l] - pm[l];
diff *= diff;
v[l] += obs_cnt * diff;
}
}
}
/* accumulate observation count for all densities */
dnom[i][j][k] += obs_cnt;
}
if (var_is_full) {
ckd_free_2d((void **)cov);
cov = NULL;
ckd_free(dvec);
dvec = NULL;
}
}
}
if (pdumpfh)
fputs("\n", pdumpfh);
return S3_SUCCESS;
}
