Our acoustical environment abounds with repetitive sounds, some of which are related to pitch perception. It is still unknown how the auditory system, in processing these sounds, relates a physical stimulus and its percept. Since, in mammals, all auditory stimuli are conveyed into the nervous system through the auditory nerve (AN) fibers, a model should explain the perception of pitch as a function of this particular input. However, pitch perception is invariant to certain features of the physical stimulus. For example, a missing fundamental stimulus with resolved or unresolved harmonics, or a low and high-level amplitude stimulus with the same spectral content–these all give rise to the same percept of pitch. In contrast, the AN representations for these different stimuli are not invariant to these effects. In fact, due to saturation and non-linearity of both cochlear and inner hair cells responses, these differences are enhanced by the AN fibers. Thus there is a difficulty in explaining how pitch percept arises from the activity of the AN fibers. We introduce a novel approach for extracting pitch cues from the AN population activity for a given arbitrary stimulus. The method is based on a technique known as sparse coding (SC). It is the representation of pitch cues by a few spatiotemporal atoms (templates) from among a large set of possible ones (a dictionary). The amount of activity of each atom is represented by a non-zero coefficient, analogous to an active neuron. Such a technique has been successfully applied to other modalities, particularly vision. The model is composed of a cochlear model, an SC processing unit, and a harmonic sieve. We show that the model copes with different pitch phenomena: extracting resolved and non-resolved harmonics, missing fundamental pitches, stimuli with both high and low amplitudes, iterated rippled noises, and recorded musical instruments.

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Acoustic pulse reflectometry (APR) has been applied extensively to tubular systems in research laboratories for purposes of measuring input impedance, bore reconstruction, and fault detection. Industrial applications have been mentioned in the literature, though they have not been widely implemented. Academic APR systems are extremely bulky, often employing source tubes of 6 m in length, which limits their industrial use severely. Furthermore, leak detection methods described in the literature are based on indirect methods, by carrying out bore reconstruction and finding discrepancies between the expected and reconstructed bore. In this paper we describe an APR system designed specifically for detecting faults commonly found in industrial tube systems: leaks, increases in internal diameter caused by wall thinning, and constrictions. The system employs extremely short source tubes, in the order of 20 cm, making it extremely portable, but creating a large degree of overlap between forward and backward propagating waves in the system. A series of algorithmic innovations enable the system to perform the wave separation mathematically, and then identify the above faults automatically with a measurement time on the order of 10 s per tube. We present several case studies of condenser tube inspection, showing how different faults are identified and reported.

Acoustic Pulse Reflectometry (APR) has been applied extensively to tubular systems in research laboratories, for purposes of measuring input impedance, bore reconstruction, and fault detection. Industrial applications have been mentioned in the literature, though they have not been widely implemented. Academic APR systems are extremely bulky, often employing source tubes of six meters in length, which limits their industrial use severely. Furthermore, leak detection methods described in the literature are based on indirect methods, by carrying out bore reconstruction and finding discrepancies between the expected and reconstructed bore. In this paper we describe an APR system designed specifically for detecting faults commonly found in industrial tube systems: leaks, increases in internal diameter caused by wall thinning, and constrictions. The system employs extremely short source tubes, on the order of 20cm, making it extremely portable, but creating a large degree of overlap between forward and backward propagating waves in the system. A series of algorithmic innovations enable the system to perform the wave separation mathematically, and then identify the above faults automatically, with a measurement time on the order of 10 seconds per tube. We present several case studies of condenser tube inspection, showing how different faults are identified and reported.

Abstract. Recent studies of the tectorial membrane (TM) revealed mechanical properties that are changing along the cochlear partition. In our previous cochlear model, the basilar membrane (BM) motion was derived from the cochlear fluid dynamics along with the outer hair cells (OHCs) electromotility force. In order to achieve a match between the resonances of both the BM and the OHCs gain, a set of constraints were obtained. In particular, the OHCs electrical properties were changed along the cochlear partition. However, although plausible differences found between conductance of the OHCs at different locations along the Cochlea, it seems negligible compared to the change in the characteristic frequency. In the current model the TM is included in the model. Since the OHCs are embedded in the TM, we assume that they are gaining their electromotility force from both the BM and TM. The electrical properties of the OHCs are held constant along the cochlear partition, while the TM stiffness and resistance are changing along the cochlear partition in correspondence to the BM dependence. The boundary conditions were derived from the middle ear model. A non-linear, odd-order, mechanism related to the OHCs motility was included in the model. The OHCs length change depends nonlinearly on its membrane electrical potential. The model was solved numerically in the time domain in response to various input signals. The basilar and tectorial membranes gain were derived for a wide range of input levels and frequencies. Both BM and TM revealed traveling waves with a maximum response for every input frequency at the same distance from the stapes. The BM sensitivity gain was greater than that of the TM. The difference between the two increased with the increase of the input level.