- Structure of
**model.outmid** - Structure of
**model.cochlea** - Structure of
**model.haircell** - Structure of model.neural
- Structure of model.pp

Structure of the profile description

The five main fields are

model.outmid | Outer and middle ear model, e.g., a fixed filter |

model.cochlea | Cochlear filtering, e.g., a gammatone filterbank |

model.haircell | mechanical-to-neural transduction, e.g., an inner hair cell model |

model.neural | Neural processing, e.g., model for neural adaptation |

model.pp | Post-processing, e.g., scaling or mapping to a decibel scale |

All main fields have several sub-fields.

- 1.
- If this field is defined as
**model.outmid.file='filename';****AudMod**loads in the file named**filename.mat**and uses the obtained*filter coefficients*to filter the signal using the following Matlab command`signal=filter(a,b,signal);`. It is important that the names of the forward and backward filter coefficients are`a`and`b`. Typically, the filter coefficients can be designed using**Make_OEM**function which is introduced later in this document.Using

**Make_OEM**it is also possible to design*frequency-warped*outer and middle ear filters. To utilize this feature, one have to download**WarpTB**package which is a set of routines for frequency-warped signal processing. - 2.
- Alternatively (you cannot use both),
**model.outmid.function='filename';****signal=MyFunction(signal);**

- 1.
- If there is a field
**model.cochlea.gt****AudMod**uses**Gammatone**function which contains the design and implementation of a gammatone filterbank. The parameters of this filterbank are transmitted in the sub-fields of**model.cochlea.gt**. This is used in all ready-made profiles. However, it may be computationally inefficient because it also contains the design of the filterbank. The design parameters for**Gammatone**function are introduced later in this document. - 2.
- In using a gammatone filterbank model for cochlear filtering
it is suggested to design a filterbank using
**Make_GTbank**routine (see below) in advance, store the filter coefficients into a .mat-file, and then define the cochlea field in the following way:**model.cochlea.fb='filename'****filename**is a .mat file containing the coefficients of the filters as row vectors in matrices**f**and**b**. - 3.
- Alternatively,
**model.cochlea.function='filename';****signal=MyFunction(signal);** - 4.
- It is possible to add a time-varying asymmetric compensation
filterbank to the output channels a cochlear model. This is based a
model introduced by Irino and Patterson [6]. The function
is activated if the field
**model.cochlea.asymmcomp**

- 1.
- In many auditory models, this phase is implemented as
a
*rectify-compress-filter*system. This function is activated in**AudMod**if the following field exists:**model.haircell.rcf**- (a)
**model.haircell.rcf.r**defines the type of rectification. There are three alternatives: 'full', 'half', and 'no', implementing full-wave rectification, half-wave rectification, or no rectification, respectively.- (b)
**model.haircell.rcf.c**defines the compression function that is applied to the rectified channel signals. Currently, there are two alternatives:**model.haircell.rcf.c='Plack98'**which implements a nonlinear compression function introduced in [2] and**model.haircell.rcf.c=c**which implements a classical compression rule*y*=*x*^{c}for all sample values. Typically,*c*=0.7.- (c)
**model.haircell.rcf.f**has currently two alternatives. If**model.haircell.rcf.f='1kHz'**the channel signals are filtered using a lowpass filter with a cut-off frequency at 1 kHz (for a sampling rate given in**model.fs**). Alternatively,**model.haircell.rcf.f='tw20'**causes the rectified and compressed channel signals to be filtered using a first order integrator with a time constant of 20 ms.

- 2.
- If field
**model.haircell.ihc**exists,**AudMod**uses Meddis's inner haircell and synapse model, see, e.g., [5]. By default, Meddis's parameter set for*medium spontaneous rate fibres*. It is also possible to define other parameter sets in an additional field**model.haircell.ihc.params**. This is given as a parameter vector and its structure becomes clear by comparing [7] with the source file Meddis_network91M.c. In future versions of this package there are going to be automatic functions for the design of different parameter sets for Meddis's model. In addition, if**model.haircell.ihc.refractory**exists, the outputs of the IHC model are processed using a model for neural refractoriness [5]. - 3.
- As in other main fields it is possible to use
**model.haircell.function='filename'** - 4.
- In some cases it is convenient to threshold the channel signal
at this phase, e.g., to get rid of negative or zero values. If
**model.haircell.threshold=b**, all signal values*below***b**are changed to**b**.

- 1.
**model.neural.function='Meddis91';****AudMod**uses Meddis's model [5] for neural refractoriness. This is the same element which also appears if**model.haircell.refractory**exists.- 2.
**model.neural.function='Plack98'**This is an efficient implementation of a*temporal window model*of neural adaptation introruced in [2].- 3.
**model.neural.function='Dau96'**This uses a nonlinear adaptation network introduced in [3]. If this model is chosen, one must also set**model.neural.Dau.thr**to some small positive value.- 4.
**model.neural.function='Karjalainen96'**This implements a nonlinear adaptation network which was introduced in [4].- 5.
- As in all other main fields
**model.neural.function='filename'**

- 1.
**model.pp.mapping='decibel'**causes the output values of the previous stages to be mapped to the decibel scale.- 2.
**model.pp.mapping='filename'**is essentially the same as the**function**sub-field in other main fields.