| /device/google/contexthub/firmware/os/algos/calibration/gyroscope/ |
| gyro_stillness_detect.h | 23 * is computed using non-overlapping windows of signal variance
48 // Variance threshold for the stillness confidence score.
51 // Delta about the variance threshold for calculation of the
72 // variance for the current window (used for stillness detection).
81 // Latest computed variance.
|
| gyro_stillness_detect.c | 34 // Set the delta about the variance threshold for calculation
42 // Set the variance threshold parameter for the stillness
59 // online mean and variance statistics:
88 // Reset current window mean and variance.
107 // Online window mean and variance ("one-pass" accumulation).
138 // Update the final calculation of window mean and variance.
162 // Define the variance thresholds.
173 // Sensor variance exceeds the upper threshold (i.e., motion detected).
181 // Sensor variance is below the lower threshold (i.e., stillness
|
| /external/apache-commons-math/src/main/java/org/apache/commons/math/stat/regression/ |
| GLSMultipleLinearRegression.java | 36 * whose variance is
103 * Calculates the variance on the beta.
107 * @return The beta variance matrix
118 * Calculates the estimated variance of the error term using the formula
125 * @return error variance
|
| /external/autotest/client/site_tests/video_WebRtcCamera/ |
| ssim.js | 29 // square root. The latter is actually an unbiased estimate of the variance,
30 // not the exact variance.
43 return {mean : meanA, variance : accu / a.length};
70 var sigmaX2 = statsX.variance;
74 var sigmaY2 = statsY.variance;
|
| /external/autotest/client/site_tests/video_WebRtcPeerConnectionWithCamera/ |
| ssim.js | 29 // square root. The latter is actually an unbiased estimate of the variance,
30 // not the exact variance.
43 return {mean : meanA, variance : accu / a.length};
70 var sigmaX2 = statsX.variance;
74 var sigmaY2 = statsY.variance;
|
| /external/libmpeg2/common/x86/ |
| icv_variance_ssse3.c | 26 * This file contains the functions to compute variance
60 * Computes variance of a given 8x4 block
63 * Compute variance of a given 8x4 block
78 * Variance
153 /* Compute variance */
|
| /cts/apps/CameraITS/tests/scene1/ |
| test_dng_noise_model.py | 25 DIFF_THRESH = 0.0012 # absolute variance delta threshold
26 FRAC_THRESH = 0.2 # relative variance delta threshold
35 # defined as being within an absolute variance delta or relative variance
36 # delta of the expected variance, whichever is larger. This is to allow the
93 # non-uniform lighting or vignetting doesn't affect the variance
117 pylab.ylabel('Center patch variance')
|
| /external/apache-commons-math/src/main/java/org/apache/commons/math/stat/descriptive/moment/ |
| Skewness.java | 107 double variance = moment.m2 / (moment.n - 1); local
108 if (variance < 10E-20) {
113 ((n0 - 1) * (n0 -2) * FastMath.sqrt(variance) * variance);
172 final double variance = (accum - (accum2 * accum2 / length)) / (length - 1); local
179 accum3 /= variance * FastMath.sqrt(variance);
|
| /external/tensorflow/tensorflow/core/kernels/ |
| fused_batch_norm_op.h | 32 // Details: in cuDNN v4, y = bnScale * (x - mean) * variance + bnBias;
33 // in v5, y = bnScale * (x - mean) / sqrt(variance + epsilon) + bnBias
38 void operator()(const Eigen::GpuDevice& d, const T* variance, double epsilon,
42 // This function converts the inverted variance of the cuDNN forward training
43 // output to variance for TensorFlow to calculate the running variance.
49 int channels, T* variance);
|
| /external/apache-commons-math/src/main/java/org/apache/commons/math/stat/descriptive/ |
| SummaryStatistics.java | 26 import org.apache.commons.math.stat.descriptive.moment.Variance;
45 * default implementation for the variance can be overridden by calling
67 /** SecondMoment is used to compute the mean and variance */
91 /** variance of values that have been added */
92 protected Variance variance = new Variance(); field in class:SummaryStatistics
115 /** Variance statistic implementation - can be reset by setter. */
116 private StorelessUnivariateStatistic varianceImpl = variance;
154 // If mean, variance or geomean have been overridden
[all...] |
| /external/autotest/server/tests/netpipe/ |
| netpipe.py | 7 def run_once(self, pair, buffer, upper_bound, variance):
43 buffer, upper_bound, variance,
46 buffer, upper_bound, variance,
|
| /external/tensorflow/tensorflow/contrib/tensor_forest/kernels/v4/ |
| stat_utils.h | 33 // Returns the variance in stats for the given output.
34 float Variance(const LeafStat& stats, int output);
36 // Returns the variance sum for all outputs.
|
| /external/tensorflow/tensorflow/core/api_def/base_api/ |
| api_def_QuantizedBatchNormWithGlobalNormalization.pbtxt | 44 A 1D variance Tensor with size matching the last dimension of t.
52 The value represented by the lowest quantized variance.
58 The value represented by the highest quantized variance.
|
| /external/tensorflow/tensorflow/python/ops/ |
| batch_norm_benchmark.py | 39 def batch_norm_op(tensor, mean, variance, beta, gamma, scale):
45 variance, beta, gamma,
51 # batch_norm = (tensor - mean) * tf.rsqrt(variance + 0.001)
55 def batch_norm_py(tensor, mean, variance, beta, gamma, scale):
57 return nn_impl.batch_normalization(tensor, mean, variance, beta, gamma if
61 def batch_norm_slow(tensor, mean, variance, beta, gamma, scale):
62 batch_norm = (tensor - mean) * math_ops.rsqrt(variance + 0.001)
99 mean, variance = nn_impl.moments(tensor, axes, keep_dims=keep_dims)
102 variance = array_ops.ones(moment_shape)
106 tensor = batch_norm_py(tensor, mean, variance, beta, gamma, scale
[all...] |
| /libcore/support/src/test/java/tests/util/ |
| SummaryStatistics.java | 26 /** Use the first value to shift all values to it when computing variance, as it improves
27 * numerical stability. Note variance is invariant to shifting. */
56 /** Variance of the values seen. */
|
| /external/tensorflow/tensorflow/contrib/bayesflow/python/ops/ |
| mcmc_diagnostics_impl.py | 45 with the same variance as `state`.
51 ```Variance{ N**-1 * Sum{X_i} } = ESS**-1 * Variance{ X_1 }.```
78 mean, variance = tf.nn.moments(states, axis=0)
79 standard_error = tf.sqrt(variance / ess)
83 `R_k := Covariance{X_1, X_{1+k}} / Variance{X_1}`, we have
209 Specifically, R-hat measures the degree to which variance (of the means)
263 `N, C --> infinity`, with `E`, `Var` denoting expectation and variance,
267 Using the law of total variance, the numerator is the variance of the combine
[all...] |
| /external/libmpeg2/common/arm/ |
| icv_variance_a9.s | 26 @* This file contains definitions of routines for variance caclulation
42 @* @brief computes variance of a 8x4 block
46 @* This functions computes variance of a 8x4 block
61 @* variance value in r0
|
| /external/libmpeg2/common/armv8/ |
| icv_variance_av8.s | 25 //* This file contains definitions of routines for variance caclulation
41 //* @brief computes variance of a 8x4 block
45 //* This functions computes variance of a 8x4 block
60 //* variance value in x0
|
| /external/libmpeg2/common/ |
| icv_variance.h | 26 * This file contains the functions to compute variance
|
| /external/libvpx/libvpx/vp9/common/ |
| vp9_mfqe.h | 23 // the current block and correlated block, the variance of the block
|
| /external/libvpx/libvpx/vp9/encoder/ |
| vp9_firstpass.h | 60 double intra_count_low; // Coded intra but low variance
61 double intra_count_high; // Coded intra high variance
86 double pcnt_intra_low; // Coded intra but low variance
87 double pcnt_intra_high; // Coded intra high variance
|
| /external/tensorflow/tensorflow/compiler/xla/service/gpu/ |
| cudnn_batchnorm_rewriter.h | 41 // call returns 1/sqrt(variance + epsilon), while the HLO returns plain
42 // variance. Similarly, the grad cudnn call expects 1/sqrt(variance + epsilon)
43 // as input, whereas the HLO expects plain variance.
|
| /external/webrtc/webrtc/test/ |
| statistics.h | 25 double Variance() const;
|
| /external/webrtc/webrtc/voice_engine/test/auto_test/standard/ |
| video_sync_test.cc | 58 // Computes the standard deviation by first estimating the sample variance
66 float variance = 0; local
68 variance += (*start - mean) * (*start - mean) / (num_elements - 1);
70 return sqrt(variance);
|
| /external/apache-commons-math/src/main/java/org/apache/commons/math/stat/clustering/ |
| KMeansPlusPlusClusterer.java | 27 import org.apache.commons.math.stat.descriptive.moment.Variance;
41 /** Split the cluster with largest distance variance. */
64 * algorithm iterations is to split the cluster with largest distance variance.
201 * Get a random point from the {@link Cluster} with the largest distance variance.
213 // compute the distance variance of the current cluster
215 final Variance stat = new Variance();
219 final double variance = stat.getResult(); local
221 // select the cluster with the largest variance
222 if (variance > maxVariance)
[all...] |
