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Nervous system conveys information by electrical signals called `spikes', therefore, spikes detection and sorting are challenging topics in the neural data processing. The principal component analysis (PCA) is a convenient tool for clustering spikes; however it has some disadvantages for closely shaped and overlapped spikes. For such the cases, an algorithm based on the combination of the principal...
A temporal point process is a stochastic time series of binary events that occurs in continuous time. In computational neuroscience, the point process is used to model neuronal spiking activity; however, estimating the model parameters from spike train is a challenging problem. The state space point process filtering theory is a new technique for the estimation of the states and parameters. In order...
Recording of neural response to specific stimulus in a repeated trial is very common in neuroscience protocol. The perstimulus time histogram (PSTH) is a standard tool for analysis of neural response. However it could not capture the non-deterministic properties of the neuron especially in higher level cortical area such as inferior temporal cortex. The stochastic state point process filter theory...
The aim of this work is to provide a quantitative approach to the problem of matching a mother wavelet to Transient Evoked Otoacoustic Emission (TEOAE) signals by using tuning. A tuning curve was used as a template for designing a mother wavelet that has the maximum matching to the tuning curve. The scaling function was calculated from the matched mother wavelet and by using these functions, lowpass...
Otoacoustic emission is low-level acoustic signal generated in cochlea and could be measured with sensitive probe in the outer ear canal. Since it was believed that the outer hair cells are the origin of otoacoustic emission and this sound is transmitted through oval window to outer ear canal, the distortion effect of middle ear and outer ear on recorded signal is inevitable. For estimating the original...
The auditory periphery system receives a one dimensional acoustical signal that describes how the local pressure varies with time. However, this one dimensional signal information is then somehow unfolded into a two dimensional time-frequency plane, that tells us when which frequency occurs. The hearing process is based on compromise between time localization and frequency localization. A kind of...
The auditory periphery system receives a one dimensional acoustical signal that describes how the local pressure varies with time. However, this one dimensional signal information is then somehow unfolded into a two dimensional time-frequency plane, that tells us when which frequency occurs. The hearing process is based on compromise between time localization and frequency localization. A kind of...
The auditory periphery system receives a one dimensional acoustical signal that describes how the local pressure varies with time. However, this one dimensional signal information is then somehow unfolded into a two dimensional time-frequency plane, that tells us when which frequency occurs. The hearing process is based on compromise between time localization and frequency localization. A kind of...
We proposed an efficient method for classification of diffused liver diseases based on Gabor wavelet. It is well known that Gabor wavelets attain maximum joint space-frequency resolution which is highly significant in the process of texture extraction and presentation. This property has been explored here as the proposed method outperforms the classification rate obtained by using dyadic wavelets...
To improve transient evoked otoacoustic emission (TEOAE) test accuracy, a new technique in presented based on multiresolution signal decomposition. Using a wavelet function which optimized according to an active cochlear model, time frequency distribution of TEOAE is obtained. The coefficients of the filter bank are determined from Morlet mother wavelet function in the analysis section. In the synthesis...
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