def __init__(self, source, cf):
CombinedFilterbank.__init__(self, source)
source = self.get_modified_source()
## Saturation
saturation = FunctionFilterbank(source, saturation_fc,
A0=0.1, B=2000, C=1.74, D=6.87e-9)
## low pass IHC
ihc = LowPass_IHC(saturation, cf, 3800, 1, 7)
self.set_output(ihc)
def __init__(self, source, cf, update_interval=1, param=None):
CombinedFilterbank.__init__(self, source)
source = self.get_modified_source()
cf = np.atleast_1d(cf)
parameters=set_parameters(cf,param)
signal = TanCarneySignal(source, cf, update_interval, parameters)
ihc = TanCarneyIHC(signal, cf)
self.set_output(ihc)
def __init__(self, source, cf, update_interval, param=None):
CombinedFilterbank.__init__(self, source)
source = self.get_modified_source()
cf = np.atleast_1d(cf)
parameters = set_parameters(cf, param)
samplerate=source.samplerate
if int(source.samplerate)!=50000:
warnings.warn('To use the TanCarney cochlear model the sample rate should be 50kHz')
# band pass filter
signal_coef = Signal_Coefficients(cf, samplerate,parameters)
[filt_b,filt_a] = signal_coef.return_coefficients(np.zeros((1,len(cf))))
BP_signal = LinearFilterbank(source,filt_b,filt_a)
control_output = TanCarneyControl(source, cf, update_interval, parameters)
updater = Filter_Update(BP_signal, signal_coef) #instantiation of the updater for the signal path
output = ControlFilterbank(BP_signal, control_output, BP_signal,
updater, update_interval) #controler for the band pass filter of the signal path
self.set_output(output)
def __init__(self, source, cf, update_interval, param=None):
CombinedFilterbank.__init__(self, source)
source = self.get_modified_source()
cf = np.atleast_1d(cf)
samplerate=source.samplerate
parameters = set_parameters(cf, param)
##### Control Path ####
# band pass filter
control_coef = Control_Coefficients(cf, samplerate)
[filt_b,filt_a] = control_coef.return_coefficients(np.zeros((1,len(cf))))
BP_control = LinearFilterbank(source,filt_b,filt_a)
# first non linearity of control path
Acp,Bcp,Ccp=100.,2.5,0.60
func_NL1_control=lambda x:np.sign(x)*Bcp*np.log(1.+Acp*abs(x)**Ccp)
NL1_control=FunctionFilterbank(BP_control,func_NL1_control)
# second non linearity of control path
asym,s0,x1,s1=7.,8.,5.,3.
shift = 1./(1.+asym)
x0 = s0*np.log((1.0/shift-1)/(1+np.exp(x1/s1)))
func_NL2_control=lambda x:(1.0/(1.0+np.exp(-(x-x0)/s0)*(1.0+np.exp(-(x-x1)/s1)))-shift)*parameters['nlgain']
NL2_control=FunctionFilterbank(NL1_control,func_NL2_control)
#control low pass filter (its output will be used to control the signal path)
gain_lp_con = (2*pi*parameters['fc_LP_control'])**3*1.5
LP_control = LowPass_filter(NL2_control,cf,parameters['fc_LP_control'],gain_lp_con,3)
#low pass filter for feedback to control band pass (its output will be used to control the control path)
gain_lp_fb = parameters['fc_LP_fb']*2*pi*10
LP_feed_back = LowPass_filter(LP_control,cf,parameters['fc_LP_fb'],gain_lp_fb,1)
updater = Filter_Update(BP_control, control_coef) #instantiation of the updater for the control path
output = ControlFilterbank(LP_control, LP_feed_back, BP_control,
updater, update_interval) #controler for the band pass filter of the control path
self.set_output(output)
