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  /prebuilts/gcc/linux-x86/host/i686-linux-glibc2.7-4.4.3/sysroot/usr/include/linux/
serial_core.h 84 /* Samsung S3C2410 SoC and derivatives thereof */
  /prebuilts/gcc/linux-x86/host/i686-linux-glibc2.7-4.6/sysroot/usr/include/linux/
serial_core.h 84 /* Samsung S3C2410 SoC and derivatives thereof */
  /prebuilts/gcc/linux-x86/host/x86_64-linux-glibc2.7-4.6/sysroot/usr/include/linux/
serial_core.h 84 /* Samsung S3C2410 SoC and derivatives thereof */
  /external/ceres-solver/include/ceres/
jet.h 32 // computing exact derivatives of functions.
44 // leads to a convenient method for computing exact derivatives without needing
69 // To handle derivatives of functions taking multiple arguments, different
75 // Following the technique above, to compute the derivatives df/dx and df/dy for
152 // derivatives is to use autodiff_cost_function.h, which is a wrapper around
153 // both jets.h and autodiff.h to make taking derivatives of cost functions for
496 // derivatives are sane.
rotation.h 59 // derivative, higher derivatives may have unexpected results near the origin.
68 // derivative, higher derivatives may have unexpected results near the origin.
168 // and truncating at one term, the value and first derivatives will be
215 // and truncating at one term, the value and first derivatives will be
  /external/opencv/cv/src/
cvoptflowlk.cpp 75 // 2.For calculating spatial derivatives we use 3x3 Sobel operator.
125 /* buffers derivatives product */
269 /* begin scan image, calc derivatives and solve system */
280 /*Here we calculate derivatives for line of image */
366 /* End of derivatives for line */
cvcornersubpix.cpp 195 /* calc derivatives */
  /prebuilts/gcc/linux-x86/host/i686-linux-glibc2.7-4.4.3/i686-linux/include/c++/4.4.3/tr1/
modified_bessel_func.tcc 65 * @f$ K_\nu(x) @f$ and their first derivatives
320 * derivatives @f$ i'_n(x) @f$ and @f$ k'_n(x) @f$
358 * derivatives @f$ Ai'(x) @f$ and @f$ Bi(x) @f$
  /prebuilts/gcc/linux-x86/host/i686-linux-glibc2.7-4.6/i686-linux/include/c++/4.6.x-google/tr1/
modified_bessel_func.tcc 65 * @f$ K_\nu(x) @f$ and their first derivatives
320 * derivatives @f$ i'_n(x) @f$ and @f$ k'_n(x) @f$
358 * derivatives @f$ Ai'(x) @f$ and @f$ Bi(x) @f$
  /prebuilts/gcc/linux-x86/host/x86_64-linux-glibc2.7-4.6/x86_64-linux/include/c++/4.6.x-google/tr1/
modified_bessel_func.tcc 65 * @f$ K_\nu(x) @f$ and their first derivatives
320 * derivatives @f$ i'_n(x) @f$ and @f$ k'_n(x) @f$
358 * derivatives @f$ Ai'(x) @f$ and @f$ Bi(x) @f$
  /prebuilts/ndk/5/sources/cxx-stl/gnu-libstdc++/include/tr1/
modified_bessel_func.tcc 65 * @f$ K_\nu(x) @f$ and their first derivatives
320 * derivatives @f$ i'_n(x) @f$ and @f$ k'_n(x) @f$
358 * derivatives @f$ Ai'(x) @f$ and @f$ Bi(x) @f$
  /prebuilts/ndk/6/sources/cxx-stl/gnu-libstdc++/include/tr1/
modified_bessel_func.tcc 65 * @f$ K_\nu(x) @f$ and their first derivatives
320 * derivatives @f$ i'_n(x) @f$ and @f$ k'_n(x) @f$
358 * derivatives @f$ Ai'(x) @f$ and @f$ Bi(x) @f$
  /prebuilts/ndk/7/sources/cxx-stl/gnu-libstdc++/include/tr1/
modified_bessel_func.tcc 65 * @f$ K_\nu(x) @f$ and their first derivatives
320 * derivatives @f$ i'_n(x) @f$ and @f$ k'_n(x) @f$
358 * derivatives @f$ Ai'(x) @f$ and @f$ Bi(x) @f$
  /prebuilts/ndk/8/sources/cxx-stl/gnu-libstdc++/4.4.3/include/tr1/
modified_bessel_func.tcc 65 * @f$ K_\nu(x) @f$ and their first derivatives
320 * derivatives @f$ i'_n(x) @f$ and @f$ k'_n(x) @f$
358 * derivatives @f$ Ai'(x) @f$ and @f$ Bi(x) @f$
  /prebuilts/ndk/8/sources/cxx-stl/gnu-libstdc++/4.6/include/tr1/
modified_bessel_func.tcc 65 * @f$ K_\nu(x) @f$ and their first derivatives
320 * derivatives @f$ i'_n(x) @f$ and @f$ k'_n(x) @f$
358 * derivatives @f$ Ai'(x) @f$ and @f$ Bi(x) @f$
  /prebuilts/ndk/8/sources/cxx-stl/gnu-libstdc++/4.7/include/tr1/
modified_bessel_func.tcc 65 * @f$ K_\nu(x) @f$ and their first derivatives
320 * derivatives @f$ i'_n(x) @f$ and @f$ k'_n(x) @f$
358 * derivatives @f$ Ai'(x) @f$ and @f$ Bi(x) @f$
  /external/ceres-solver/examples/
circle_fit.cc 33 // take the derivatives.
powell.cc 113 // wrapper to get the derivatives automatically. The parameters, x1 through
  /external/openssh/
ssh-agent.0 70 csh(1) and derivatives.
ssh-agent.1 158 and derivatives.
  /external/ceres-solver/internal/ceres/
gradient_checking_cost_function_test.cc 100 // in the derivatives.
103 // Accumulate 1st order derivatives.
compressed_row_jacobian_writer.cc 84 // Count the number of derivatives for a row of this residual block and
  /external/jmonkeyengine/engine/src/core-effects/Common/MatDefs/Water/
Water.frag 393 // to calculate the derivatives for all these pixels by using step()!
395 // Where the derivatives are undefined
Water15.frag 403 // to calculate the derivatives for all these pixels by using step()!
405 // Where the derivatives are undefined
  /external/ceres-solver/docs/
modeling.tex 49 If \texttt{jacobians} is \texttt{NULL}, then no derivatives are returned; this is the case when computing cost only. If \texttt{jacobians[i]} is \texttt{NULL}, then the Jacobian matrix corresponding to the $i^{\textrm{th}}$ parameter block must not be returned, this is the case when the a parameter block is marked constant.
232 place, by adding a scale factor $a > 0$ which gives us $\rho(s,a) = a^2 \rho(s / a^2)$ and the first and second derivatives as $\rho'(s / a^2)$ and $(1 / a^2) \rho''(s / a^2)$ respectively.
272 where the terms involving the second derivatives of $f(x)$ have been ignored. Note that $H(x)$ is indefinite if $\rho''f(x)^\top f(x) + \frac{1}{2}\rho' < 0$. If this is not the case, then its possible to re-weight the residual and the Jacobian matrix such that the corresponding linear least squares problem for the robustified Gauss-Newton step.

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