| /external/webrtc/webrtc/modules/audio_processing/intelligibility/ |
| intelligibility_enhancer.h | 106 // Updates variance computation and analysis with |in_block_|,
120 // Updates variance calculation for noise input with |in_block|.
134 // Computes variance across ERB filters from freq variance |var|.
|
| /external/webrtc/webrtc/modules/audio_processing/intelligibility/test/ |
| intelligibility_proc.cc | 45 "Variance algorithm for clear data.");
46 DEFINE_double(clear_alpha, 0.9, "Variance decay factor for clear data.");
49 "Window size for windowed variance for clear data.");
61 "Variance clear rate; history is forgotten every N gain recalculations.");
|
| /external/tensorflow/tensorflow/contrib/distributions/python/ops/ |
| moving_stats.py | 37 """Compute exponentially weighted moving {mean,variance} of a streaming value.
51 T. Finch, Feb 2009. "Incremental calculation of weighted mean and variance".
58 exponentially weighted moving variance. Same shape as `mean_var` and
69 exponentially weighted moving variance.
173 """Compute exponentially weighted moving {mean,variance} of a streaming value.
187 T. Finch, Feb 2009. "Incremental calculation of weighted mean and variance".
206 exponentially weighted moving variance.
|
| /external/tensorflow/tensorflow/core/kernels/ |
| mkl_fused_batch_norm_op.cc | 153 // Batch variance in TF layout
160 // output tensors for batch mean and variance.
162 // estimated mean and variance.
173 // Mean and variance (without Bessel's correction) saved for backward
174 // computation to serve as pre-computed mean and variance.
194 // Bessel's correction on variance, if training mode is on
334 inline void MklSetMeanVariance(const Tensor& mean, const Tensor& variance) {
338 static_cast<const void*>(variance.flat<float>().data()));
366 // Here scale, mean, and variance are 1D and considered
391 errors::InvalidArgument("saved variance must be 1-dimensional"
[all...] |
| /frameworks/base/media/mca/filterpacks/java/android/filterpacks/videoproc/ |
| BackDropperFilter.java | 132 // Variance threshold scale factor for large scale of hierarchy
134 // Variance threshold scale factor for medium scale of hierarchy
136 // Variance threshold scale factor for small scale of hierarchy
188 // Scale value for mapping variance distance to fit nicely to 0-1, 8-bit
190 // Scale value for mapping variance to fit nicely to 0-1, 8-bit
194 // Minimum variance (0-255 scale)
236 // Variance distance in luminance between current pixel and background model
237 "float gauss_dist_y(float y, float mean, float variance) {\n" +
238 " float dist = (y - mean) * (y - mean) / variance;\n" +
241 // Sum of variance distances in chroma between current pixel and backgroun
[all...] |
| /external/libvpx/libvpx/vpx_dsp/ |
| variance.c | 17 #include "vpx_dsp/variance.h"
52 static void variance(const uint8_t *a, int a_stride, const uint8_t *b, function
134 variance(a, a_stride, b, b_stride, W, H, sse, &sum); \
172 /* Identical to the variance call except it takes an additional parameter, sum,
180 variance(a, a_stride, b, b_stride, W, H, sse, sum); \
183 /* Identical to the variance call except it does not calculate the
192 variance(a, a_stride, b, b_stride, W, H, sse, &sum); \
196 /* All three forms of the variance are available in the same sizes. */
513 /* All three forms of the variance are available in the same sizes. */
|
| /external/apache-commons-math/src/main/java/org/apache/commons/math/stat/descriptive/ |
| AggregateSummaryStatistics.java | 198 * {@inheritDoc}. This version returns the variance of all the aggregated
332 final double variance; local
334 variance = Double.NaN;
336 variance = 0d;
338 variance = m2 / (n - 1);
340 return new StatisticalSummaryValues(mean, variance, n, max, min, sum);
|
| /frameworks/base/tests/Camera2Tests/SmartCamera/SimpleCamera/src/androidx/media/filterfw/samples/simplecamera/ |
| ImageGoodnessFilter.java | 281 return BIG_SCORE_INC; // low variance, sharpness above the mean
306 return BIG_SCORE_INC; // low variance, underExposure below the mean
331 return BIG_SCORE_INC; // low variance, overExposure below the mean
356 return BIG_SCORE_INC; // low variance, contrast above the mean
381 return BIG_SCORE_INC; // low variance, colorfulness above the mean
406 return BIG_SCORE_INC; // low variance, brightness above the mean
|
| /art/libartbase/base/ |
| histogram.h | 58 double Variance() const;
120 // Summation of the values entered. Used to calculate variance.
|
| /cts/apps/CameraITS/tests/scene1/ |
| test_raw_sensitivity.py | 59 # Measure the variance. Each shot should be noisier than the
92 pylab.ylabel("Image Center Patch Variance")
|
| /external/libvpx/libvpx/vp8/common/ |
| loopfilter_filters.c | 37 /* is there high variance internal edge ( 11111111 yes, 00000000 no) */
57 /* add outer taps if we have high edge variance */
95 int hev = 0; /* high edge variance */
119 int hev = 0; /* high edge variance */
149 /* add outer taps if we have high edge variance */
165 /* only apply wider filter if not high edge variance */
196 signed char hev = 0; /* high edge variance */
221 signed char hev = 0; /* high edge variance */
|
| /external/libvpx/libvpx/vp9/encoder/ |
| vp9_mcomp.h | 15 #include "vpx_dsp/variance.h"
48 // Utility to compute variance + MV rate cost for a given MV
|
| /external/tensorflow/tensorflow/contrib/tensor_forest/kernels/v4/ |
| stat_utils.cc | 53 float Variance(const LeafStat& stats, int output) {
69 sum += Variance(stats, i);
|
| /external/tensorflow/tensorflow/contrib/tensor_forest/proto/ |
| fertile_stats.proto | 46 // This is the info needed for calculating variance for regression.
47 // Variance will still have to be summed over every output, but the
|
| /external/tensorflow/tensorflow/tools/api/golden/ |
| tensorflow.distributions.-bernoulli.pbtxt | 140 name: "variance"
141 argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'variance\'], "
|
| tensorflow.distributions.-beta.pbtxt | 144 name: "variance"
145 argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'variance\'], "
|
| tensorflow.distributions.-categorical.pbtxt | 144 name: "variance"
145 argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'variance\'], "
|
| tensorflow.distributions.-dirichlet-multinomial.pbtxt | 144 name: "variance"
145 argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'variance\'], "
|
| tensorflow.distributions.-dirichlet.pbtxt | 140 name: "variance"
141 argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'variance\'], "
|
| tensorflow.distributions.-distribution.pbtxt | 131 name: "variance"
132 argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'variance\'], "
|
| tensorflow.distributions.-exponential.pbtxt | 141 name: "variance"
142 argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'variance\'], "
|
| tensorflow.distributions.-gamma.pbtxt | 140 name: "variance"
141 argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'variance\'], "
|
| tensorflow.distributions.-laplace.pbtxt | 140 name: "variance"
141 argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'variance\'], "
|
| tensorflow.distributions.-multinomial.pbtxt | 144 name: "variance"
145 argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'variance\'], "
|
| tensorflow.distributions.-normal.pbtxt | 140 name: "variance"
141 argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'variance\'], "
|
