def __init__(self):
     self.lms = DoubleLMSFilter(40)
     self.lms.input_sampling_rate = fs
     self.lms.memory = 0.999
     self.lms.mu = 0.015
     self.lms.w = np.ones((40, ))
     self.lms.learning = False
class Filter:
    def __init__(self):
        self.lms = DoubleLMSFilter(40)
        self.lms.input_sampling_rate = fs
        self.lms.memory = 0.999
        self.lms.mu = 0.015
        self.lms.w = np.ones((40, ))
        self.lms.learning = False

    def process(self, input, ref):
        import numpy as np
        output = np.zeros(input.shape, dtype=np.float64)

        infilter = DoubleInPointerFilter(input, False)
        infilter.input_sampling_rate = fs
        reffilter = DoubleInPointerFilter(ref, False)
        reffilter.input_sampling_rate = fs
        self.lms.set_input_port(0, infilter, 0)
        self.lms.set_input_port(1, reffilter, 0)
        outfilter = DoubleOutPointerFilter(output, False)
        outfilter.input_sampling_rate = fs
        outfilter.set_input_port(0, self.lms, 0)
        outfilter.process(input.shape[1])

        return output
class Filter:
  def __init__(self):
    self.lms = DoubleLMSFilter(40)
    self.lms.input_sampling_rate = fs
    self.lms.memory = 0.999
    self.lms.mu = 0.015
    self.lms.w = np.ones((40,))
    self.lms.learning = False

  def process(self, input, ref):
    import numpy as np
    output = np.zeros(input.shape, dtype=np.float64)

    infilter = DoubleInPointerFilter(input, False)
    infilter.input_sampling_rate = fs
    reffilter = DoubleInPointerFilter(ref, False)
    reffilter.input_sampling_rate = fs
    self.lms.set_input_port(0, infilter, 0)
    self.lms.set_input_port(1, reffilter, 0)
    outfilter = DoubleOutPointerFilter(output, False)
    outfilter.input_sampling_rate = fs
    outfilter.set_input_port(0, self.lms, 0)
    outfilter.process(input.shape[1])

    return output
 def __init__(self):
   self.lms = DoubleLMSFilter(40)
   self.lms.input_sampling_rate = fs
   self.lms.memory = 0.999
   self.lms.mu = 0.015
   self.lms.w = np.ones((40,))
   self.lms.learning = False
Esempio n. 5
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def filter(input, reference):
    import numpy as np
    output = np.zeros(input.shape, dtype=np.float64)

    infilter = DoubleInPointerFilter(input, False)
    infilter.input_sampling_rate = 48000
    reffilter = DoubleInPointerFilter(reference, False)
    reffilter.input_sampling_rate = 48000
    rls = DoubleLMSFilter(12)
    rls.input_sampling_rate = 48000
    rls.memory = 0.9
    rls.mu = 0.05
    rls.set_input_port(0, infilter, 0)
    rls.set_input_port(1, reffilter, 0)
    outfilter = DoubleOutPointerFilter(output, False)
    outfilter.input_sampling_rate = 48000
    outfilter.set_input_port(0, rls, 0)
    outfilter.process(input.shape[1])

    return output
def filter(input, reference):
  import numpy as np
  output = np.zeros(input.shape, dtype=np.float64)

  infilter = DoubleInPointerFilter(input, False)
  infilter.input_sampling_rate = 48000
  reffilter = DoubleInPointerFilter(reference, False)
  reffilter.input_sampling_rate = 48000
  rls = DoubleLMSFilter(12)
  rls.input_sampling_rate = 48000
  rls.memory = 0.9
  rls.mu = 0.05
  rls.set_input_port(0, infilter, 0)
  rls.set_input_port(1, reffilter, 0)
  outfilter = DoubleOutPointerFilter(output, False)
  outfilter.input_sampling_rate = 48000
  outfilter.set_input_port(0, rls, 0)
  outfilter.process(input.shape[1])

  return output
Esempio n. 7
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def LMS_bad_size_test():
    import numpy as np

    lms = DoubleLMSFilter(100)
    lms.w = np.ones((10, ))
Esempio n. 8
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def LMS_bad_dim_test():
    import numpy as np

    lms = DoubleLMSFilter(100)
    lms.w = np.array(())
 def __init__(self):
   self.lms = DoubleLMSFilter(11)
   self.lms.input_sampling_rate = fs
   self.lms.memory = 0.999
   self.lms.mu = 0.05
 def __init__(self):
     self.lms = DoubleLMSFilter(11)
     self.lms.input_sampling_rate = fs
     self.lms.memory = 0.999
     self.lms.mu = 0.05