| /external/tensorflow/tensorflow/contrib/factorization/g3doc/ |
| D | gmm.md | 1 # Gaussian Mixture Models
3 Gaussian mixture models assume that the input is generated by a mixture of a
4 finite number of Gaussian distributions with unknown parameters.
|
| /external/skia/src/gpu/effects/ |
| D | GrCircleBlurFragmentProcessor.fp | 53 // Create a Gaussian half-kernel (right side) and a summed area table given a sigma and number
95 // Apply a Gaussian at point (evalX, 0) to a circle centered at the origin with radius circleR.
96 // This relies on having a half kernel computed for the Gaussian and a table of applications of
124 // half the Gaussian and a matching summed area table. The summed area table is used to compute
155 // Ensure the tail of the Gaussian goes to zero.
198 // When sigma is really small this becomes a equivalent to convolving a Gaussian with a
200 // Guassian and the profile texture is a just a Gaussian evaluation. However, we haven't yet
|
| /external/skqp/src/gpu/effects/ |
| D | GrCircleBlurFragmentProcessor.fp | 53 // Create a Gaussian half-kernel (right side) and a summed area table given a sigma and number
95 // Apply a Gaussian at point (evalX, 0) to a circle centered at the origin with radius circleR.
96 // This relies on having a half kernel computed for the Gaussian and a table of applications of
124 // half the Gaussian and a matching summed area table. The summed area table is used to compute
155 // Ensure the tail of the Gaussian goes to zero.
198 // When sigma is really small this becomes a equivalent to convolving a Gaussian with a
200 // Guassian and the profile texture is a just a Gaussian evaluation. However, we haven't yet
|
| /external/webrtc/webrtc/base/ |
| D | random.h | 48 double Gaussian(double mean, double standard_deviation);
|
| D | random.cc | 69 double Random::Gaussian(double mean, double standard_deviation) { in Gaussian() function in webrtc::Random
|
| D | random_unittest.cc | 270 TEST(RandomNumberGeneratorTest, Gaussian) { in TEST() argument
280 int index = prng.Gaussian(kMean, kStddev) + 0.5; in TEST()
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| /external/libxcam/modules/ocl/ |
| D | cl_3a_image_processor.h | 64 Gaussian, enumerator
|
| D | cl_3a_image_processor.cpp | 303 case Gaussian: { in create_handlers()
|
| /external/webrtc/webrtc/modules/remote_bitrate_estimator/ |
| D | overuse_detector_unittest.cc | 62 random_.Gaussian(0, standard_deviation_ms) + 0.5)); in Run100000Samples()
85 random_.Gaussian(0, standard_deviation_ms) + 0.5)); in RunUntilOveruse()
127 int index = random_.Gaussian(49, 10); in TEST_F()
|
| /external/tensorflow/tensorflow/contrib/eager/python/examples/l2hmc/ |
| D | README.md | 15 including the 2D strongly correlated Gaussian and the rough well energy function,
|
| /external/tensorflow/tensorflow/core/api_def/base_api/ |
| D | api_def_ExtractGlimpse.pbtxt | 50 uniform distribution or a Gaussian distribution.
|
| /external/python/cpython2/Doc/library/ |
| D | random.rst | 18 On the real line, there are functions to compute uniform, normal (Gaussian),
251 Gaussian distribution. *mu* is the mean, and *sigma* is the standard
|
| /external/python/cpython3/Doc/library/ |
| D | random.rst | 19 On the real line, there are functions to compute uniform, normal (Gaussian),
273 Gaussian distribution. *mu* is the mean, and *sigma* is the standard
|
| /external/libxcam/tests/ |
| D | test-device-manager.cpp | 601 wdr_mode = CL3aImageProcessor::Gaussian; in main()
|
| /external/ImageMagick/MagickCore/ |
| D | resize.c | 287 static double Gaussian(const double x,const ResizeFilter *resize_filter) in Gaussian() function
864 { Gaussian, 2.0, 1.5, 0.0, 0.0, GaussianWeightingFunction }, /* Gaussian */ in AcquireResizeFilter()
1039 if ((resize_filter->filter == Gaussian) || in AcquireResizeFilter()
1040 (resize_filter->window == Gaussian) ) { in AcquireResizeFilter()
|
| /external/libxcam/ |
| D | ChangeLog | 166 neighbor pixels with a Gaussian blur filter.
|
| /external/webrtc/webrtc/modules/remote_bitrate_estimator/test/ |
| D | bwe_test_framework.cc | 397 int64_t gaussian_random = random->Gaussian(mean, std_dev); in TruncatedNSigmaGaussian()
|
| /external/tensorflow/tensorflow/contrib/kernel_methods/g3doc/ |
| D | tutorial.md | 171 Gaussian) kernel function. This function is one of the most-widely used kernel
|
| /external/libxcam/wrapper/gstreamer/ |
| D | gstxcamsrc.cpp | 994 cl_processor->set_tonemapping(CL3aImageProcessor::CLTonemappingMode::Gaussian); in gst_xcam_src_start()
|
| /external/ImageMagick/Magick++/ |
| D | ChangeLog | 1159 Gaussian blur image.
1161 * lib/Image.cpp (gaussianBlur): New method to Gaussian blur image.
|
| /external/python/cpython3/Doc/faq/ |
| D | library.rst | 831 * ``normalvariate(mean, sdev)`` samples the normal (Gaussian) distribution.
|
| /external/tensorflow/tensorflow/contrib/slim/ |
| D | README.md | 88 mechanism (e.g. randomly sampled from a Gaussian). Furthermore, if a variable
|
| /external/python/cpython2/Doc/faq/ |
| D | library.rst | 859 * ``normalvariate(mean, sdev)`` samples the normal (Gaussian) distribution.
|
| /external/python/cpython3/Doc/whatsnew/ |
| D | 3.2.rst | 1061 The :func:`~math.erf` function computes a probability integral or `Gaussian
|
| /external/jline/src/src/test/resources/jline/example/ |
| D | english.gz | |