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  /device/asus/flo/
thermald-flo.conf 0 sampling 5000
4 sampling 5000
11 sampling 1000
18 sampling 1000
25 sampling 1000
32 sampling 1000
39 sampling 1000
46 sampling 1000
53 sampling 1000
60 sampling 100
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  /device/lge/mako/
thermald-mako.conf 0 sampling 5000
4 sampling 5000
11 sampling 5000
18 sampling 5000
25 sampling 5000
32 sampling 5000
39 sampling 5000
46 sampling 5000
53 sampling 5000
60 sampling 500
    [all...]
  /external/v8/tools/
process-heap-prof.py 53 sampling = False
71 sampling = True
74 sampling = False
75 elif row[0] == itemname and sampling:
  /external/speex/libspeex/
filterbank.h 52 FilterBank *filterbank_new(int banks, spx_word32_t sampling, int len, int type);
filterbank.c 54 FilterBank *filterbank_new(int banks, spx_word32_t sampling, int len, int type)
62 df = DIV32(SHL32(sampling,15),MULT16_16(2,len));
63 max_mel = toBARK(EXTRACT16(sampling/2));
  /external/ceres-solver/docs/
curvefitting.tex 5 \texttt{examples/data\_fitting.cc}. It contains data generated by sampling the curve $y = e^{0.3x + 0.1}$ and adding Gaussian noise with standard deviation $\sigma = 0.2$.}. Let us fit some data to the curve
73 \caption{Least squares data fitting to the curve $y = e^{0.3x + 0.1}$. Observations were generated by sampling this curve uniformly in the interval $x=(0,5)$ and adding Gaussian noise with $\sigma = 0.2$.\label{fig:exponential}}
  /external/webkit/Tools/Scripts/
run-sunspider 62 --shark20 Like --shark, but with a 20 microsecond sampling interval
  /external/webkit/PerformanceTests/SunSpider/
sunspider 59 --shark20 Like --shark, but with a 20 microsecond sampling interval

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