Head-related transfer function software

head-related transfer function software Head-Related Transfer Functions To find the sound pressure that an arbitrary source x(t) produces at the ear drum, all we need is the impulse response h(t) from the source to the ear drum. This is called the Head-Related Impulse Response (HRIR), and its Fourier transform H(f) is called the Head Related Transfer Function (HRTF). Modify the 3-D audio image of a sound file by filtering it through a head-related transfer function (HRTF). Set the location of the sound source by specifying the desired azimuth and elevation. load 'ReferenceHRTF.mat' hrtfData sourcePosition hrtfData = permute(double(hrtfData),[2,3,1]); sourcePosition = sourcePosition(:[1,2]);. Head-Related Transfer Function and Virtual Auditory Display covers binaural hearing and the basic principles, experimental measurements, computation, physical characteristics analyses, filter design, and customization of HRTFs. Part of the magic of a good 3D audio reproduction involves the so-called, “head-related transfer functions” (HRTFs). HRTFs describe the unique pattern of how acoustic waves propagate to a listener’s ear drums, being acoustically filtered by the listener’s ears, head, and torso on the way.

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head-related transfer function software

head-related transfer function software

Head-Related Transfer Function and Virtual Auditory Display

To speed up the HRTF measurement, the multiple exponential sweep method A head-related transfer function (HRTF) describes the sound transmission from in electrical hearing. During his studies he developed software and hardware.by P MAJDAK · ‎2007 · ‎Cited by 197 · ‎Related articles.

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head-related transfer function software

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Head-related transfer functions (HRTFs) describe the listener-specific In most of these studies, researchers either had to use commercial software or to  ‎About · ‎Features · ‎License · ‎References. HRTF HRIR Sound Localization Pinna Signal Decomposition Adaptive System Computing Sciences and Software Engineering, K. Elleithy, Ed. Netherlands:  by KJ Faller · ‎2008 · ‎Related articles.

Head-related transfer functions (HRTFs) describe the listener-specific In most of these studies, researchers either had to use commercial software or to  ‎About · ‎Features · ‎License · ‎References. HRTF HRIR Sound Localization Pinna Signal Decomposition Adaptive System Computing Sciences and Software Engineering, K. Elleithy, Ed. Netherlands:  by KJ Faller · ‎2008 · ‎Related articles.

PERSONALIZED HEAD RELATED TRANSFER FUNCTION (HRTF) BASED ON VIDEO CAPTURE - EmbodyVR, Inc.

Head-Related Transfer Function

Software and modelling of head-related transfer function for spatial audio synthesis

There has been a growing interest in spatial sound generation arising from the de- velopment of new communications and media technologies. Binaural spatial sound systems are capable of encoding and rendering sound sources accurately in three di- mensional space using only two recording/playback channels. This is based on the concept of the Head-RelatedTransferFunction (HRTF ), which is a set of acoustic filters from the you idm mien phi 2015 with source to a listener’s eardrums and contains all the listening cues used by the hearing mechanism for decoding spatial information encoded in binaural signals. The HRTF is usually obtained from acoustic measurements on dif- ferent persons. In the case of discrete data and sets of measurements corresponding to different human subjects, it is desirable to have a continuous functional repre- sentation of the HRTF for efficiently rendering moving sounds in the virtual spatial audio systems; further this representation should be well-suited for customization to an individual listener.
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software Experimental guided spherical harmonics based head related transfer function modeling

In this thesis we investigate the experimental guided spherical harmonics based Head-RelatedTransferFunction (HRTF) modeling where HRTFs are parameter- ized as frequency and source location. We focus on efficiently representing the HRTF variations in sufficient detail by mathematical modeling and the experimen- tal measurements. The goal of this work is towards an optimal functional HRTF modeling taking into account the demands of decreasing the computational cost and alleviating the HRTF interpolation and/or extrapolation in the headphone based binaural systems.

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Efficient and compact representations of head related transfer functions

J. Sinker Compact HRTFs CHAPTER 7. DISCUSSION show a recurring increase in reconstruction/modelling error of HRTFs at contralateral an- gles. This phenomenon has been addressed by many authors, and is consistently attributed to the comparatively low signal level at the occluded ear for source positions on or close to the inter aural axis, and the relative complexity of the spectral shapes at these positions, due to diffraction around the head [Kulkarni et al., 1999] [Chen et al., 1995] [Zhang, 2009]. For the purposes of ITD estimation or extraction, it is possible that HRIR measurement could be conducted using a higher level acoustic stimulus, such that the lower level signal measured at contralateral positions is sufficiently clear of the system noise floor. This would attempt to reduce the inaccuracies of the ITD extraction methods that likely occur as a result https://roaden.click/news-magazines/dbisam-for-delphi-7.php the lower signal to noise https://roaden.click/news-magazines/jikuu-tantei-genshi-kun-adobe.php. However a global level adjustment as described would provide no improvement in the reconstruction/modelling error that occurs due to the increased spectral complexity and relatively lower level of contralateral measurements. Possible improvements may be achievable in the reconstruction or modelling of contralateral positions should they be given a weighted emphasis during processing. In particular for the decompositional pro- cess; a boost in the relative level of the contralateral measurements would serve to add ’importance’ to them, increasing their share of the total variance of the dataset. Hence during decomposition the more complex spectral shapes, that occurred previously only at relatively low levels, would be better represented by the lower order principal components, or perhaps orthogonal K coefficients. Such a method would likely result in an increased number of principal components or K coefficients required in order to capture the whole variance of the dataset, and of course an appropriate inverse weighting after reconstruction, but should serve to increase the reconstruction or modelling accuracy of the contralateral positions. Chen et al. suggested similarly that the contralateral data could be weighted upon the construction of the PCA covariance matrix, however they did not attempt to implement such an optimisation [Chen et al., 1995].
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Loudness stability of binaural sound with spherical harmonic representation of sparse head-related transfer functions

To evaluate the effect of the sparsity, aliasing, and trunca- tion errors on the interpolated HRTF, a numerical analysis of these errors is presented for the representative case of KEMAR’s HRTF [41]. Note that although the HRTF of KEMAR was used for all the numerical analysis pre- sented in this section and in Section 5, similar results were obtained using the HRTFs of two other manikins: Neu- mann KU-100 [42] and FABIAN [43], although these are not presented here due to space constraints. The HRTF of KEMAR was simulated using the boundary element method, implemented by OwnSurround Ltd. [44], based on a 3D scan of the head and torso of a KEMAR. The 3D scan was acquired using Artec Eva and Artec Spider scan- ners, with a precision of 0.5 mm for the head and torso and 0.1 mm for the pinna. The simulated frequencies were in the range of 50 Hz to 24 kHz with a resolution of 50 Hz. A total of Q = 2030 directions were simulated in accordance with a Lebedev sampling scheme [45], which can provide HRTFs up to a spatial order of 38. Subsets from this simu- lation, chosen according to nearly uniform [46] ( λ = 1.5) and extremal [47] (λ = 1) sampling schemes, were used as the sparse HRTF sets. All sampling schemes lead to a SH matrix Y with a condition number below 3.5, which means that no ill-conditioning problems were introduced in the matrix inversion operation that is presented as part of Eq. (5).
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Auditory Source Localization by Time Frequency Analysis and Classification of Electroencephalogram Signals

Two classes of 2 secs stimuli were applied randomly. The first is a pure tone of 3 kHz with 500 ms increasing tone, steady during 1 second, and then transfer tone during 500ms. The second stimulus was a burst of 3 kHz pure tone with durations of 100ms ON, and 100ms OFF for 10 trials. This give a total of 224 auditory stimuli (112 right/112 left). Each series of 16 stimuli takes around 2 minutes and the participant is allowed one minute to rest between trials. The sound stimuli were presented through a program written in Matlab (Figure 1). The National Instruments device was used to put markers in the EEG data as they were recorded simultaneously when auditory stimuli were presented. The results presented in this paper are from the analysis of EEG data collected from 3 different subjects. Apart from 2 directions of Left and Right for sound stimulus presentation, head-related direction stimuli were also presented to the subjects. For the four direction sound data presentation, we used sound localization using the headrelatedtransferfunction. The HeadRelatedTransferFunction (HRTF) is a novel technique to simulate direction of arrival of sounds. HeadRelatedTransfer
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Point Spread Function and Modulation Transfer Function Engineering

An experimental setup was designed to test the PSF engineered imaging system using a spatial light modulator as a digitally-controlled arbitrary phase mask. The spatial light modulator, a reflective and diffractive surface, provided challenges which would not be present with a static transparent phase mask. Methods for overcoming these challenges met and limitations on field of view and spectral bandwidth of the scene were made. Previously know axicon, cubic, and vortex phase functions were tested to image a resolution bar target in the presence of a laser to both validate the proposed imaging system and test if the odd cubic function outperforms the even axicon and vortex functions. Each mask successfully restored an image of the target while reducing the peak irradiance of the laser by a factor of 50. The cubic provided both high resolution and less noisy restored image. The joint deconvolution method was also validated by combining exposures using the vortex and axicon phase mask to greatly reduce the noise gain.
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Model Order Reduction by Routh Stability Array with Stability Equation Method for SISO and MIMO Systems

All the control system and power system networks de- fined in MATLAB using a block diagram in SIMULINK portion may represent a higher-order connect azure tool directory active for that system [4]. This transferfunction for the sim- plicity or for ease of operation must be reduced to a lower-order transferfunction using a reduction tech- nique prevalent in literature such as Routh approxima- tion [5], Pade approximation [6], Routh-Pade method [7, 8], Stability equation method [9, 10, 11, 12], Dif- ferentiation method [2, 3, 4, 13], Routh Stability array method [10, 14], pole clustering [15], integral square er- ror method [1] and/or based on soft computing tech- niques such as genetic algorithm (GA) [16, 17], parti- cle swarm optimization (PSO) [18, 19], bat algorithm (BA)[1] and Harmony search algorithm [7] etc.
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Bicycle accident-related head injuries in India.

Objectives: To describe the epidemiology of head injuries sustained due to bicycle accidents in India. Materials and Methods: Data were retrospectively collected over a period of six months (15 May 2011 to 15 November 2011). Demography of patients, Glasgow coma scale (GCS), clinical and imaging findings, and mortality and outcome using Glasgow outcome scale (GOS), Rivermead post‑concussion symptom function (RPCSQ) and Rivermead head injury follow‑up questionnaire (RHFUQ), were analyzed. Outcome was assessed by telephonic interview. Results: There were 108 patients (100 males) with mean age of 27.7 years. Seventy‑four (68.5%) were from rural areas. Accidents due to vehicular collision accounted for 60 (55.6%) cases. None wore a helmet. The admission GCS was 14‑15 in 68.5% cases, 13‑3 in 31.5%. The risk of moderate to severe injuries was increased among working laborers (OR = 5), and patients with loss of consciousness (OR = 4). Sixty‑three (49%) patients had abnormal computed tomography (CT) findings; most common finding was skull fracture 25 (23.1%). Four patients needed surgery. The GOS assessment at three to six months revealed favorable outcome in 66 patients (61.1%) and death in 8 (7.4%). The common post‑concussion symptoms were headache, fatigue, and poor concentration. Conclusion: The majority of hospitalized cyclists were from a rural background and of the lower income group. After three months the majority of patients had good recovery with few persistent concussion symptoms.
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MAGNIFYING THE ENDURANCE OF NETWORK SECURITY BY DESTINATION SEQUENCED DISTANCE VECTOR PROTOCOL USING Read more THEORY TECHNIQUES IN NETWORKING

b. Distribution normalized algorithm: Distributed normalized algorithm will detect the IDS nodes from one network to another network while packet transmission. As well as the main security of network lifetime maximizes while base station transfer the queries with answer to all the cluster heads after every cycling process differently question and answer arises. This can be cluster head security maintenance from transfer the base station monitoring. And further any of the mobile nodes will switch over into the any other cluster means then those moving mobile sensor nodes cluster authorization provide from this cluster to another cluster heads. So we can easily detects the mobile sensor nodes easily for already registered or not.
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Digital Filter

Types of digital filter : Many digital filters are based on the fast Fourier transform, a mathematical algorithm that quickly extracts the frequency spectrum of a signal, click the following article allowing the spectrum to be manipulated (such as to create band-pass filters) before converting the modified spectrum back into a time-series signal. Another form of a digital filter head-related that of a state- space model. Turma do querubim adobe well used state-space filter is the Kalman filter published by Rudolf Kalman in 1960.Traditional linear filters are usually based on attenuation. Alternatively nonlinear filters can be designed, including energy transfer filters [10] which
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Online Full Text

In Fig. 10, the queue evolution of the non-linear model of the network working with TCPW is shown. The queue evolution, when the controller is the one tuned, considering no delay in the plant is bad. The same can be said about the discarding probability (Fig. 11). Moreover, if we compare the results of the linear and the non-linear simulation, there are many differences. We can conclude that the controller was validated using the transferfunction and no delay and this does not correspond to reality.

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Magnetization transfer contrast MR in lesions of the head and neck

The concept of magnetization transfer (MT) and its application to magnetic resonance (MR) imaging have been described in detail else- where (1, 2). In brief, selective magnetization of protons associated with macromolecules may be transferred to the water proton population that constitutes the MR image. Where an effi- cient transfer mechanism exists between the two proton populations, a strong MT effect is observed. In the resultant image, the MT effect is seen as a reduction in signal intensity. Exam- ples of tissues that exhibit a strong MT effect include muscle, cartilage, and brain paren-
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STRAIN TRANSFER FUNCTION IN FLEXIBLE PAVEMENTS

Structural failure of anflexible pavement is primarily caused due to fatigue and rutting failures. To measure fatigue performances, the critical horizontal tensile strain (  t ) at the see more of flexible layer is popularly used in the mechanistic-empirical (M-E) pavement design process. However, the computation of  t in a 3-D multilayered pavement structure with distributed loading is a complex phenomenon. This paper attempts to present simple strain transfer functions for estimation of  t considering 3-D nonlinear analysis of flexible pavements. The transferfunction is validated and found adequate in prediction of  t. Degree of accuracy has also beenjustified statistically. ABAQUS software is used for analysis of pavement structures.
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Evaluating the use of testate amoeba for palaeohydrological reconstruction in permafrost peatlands

Although the European (ACCROTELM) transferfunction works well for the major hydrological change in the peat profile it performs relatively poorly for the independent contemporary samples due to missing or poor quality analogues caused by taxa only being in a small number of samples (Figure 6, Supplementary file 6). Several taxa are relatively common in the Abisko peatlands that are not well- represented in the European transferfunction (e.g. Arcella hemisphaerica, Arcella gibossa type, Cryptodifflugia oviformis and Placocista spinosa). Thus, we suggest that the European model is less applicable to high-latitude peatlands, highlighting the importance of our development of a high- latitude model.
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ThisThingCallControl!

We take note that the highest power of s is two. And we take the inverse Laplace transform of this function, we see that the response is not necessarily an exponential function. It can be exponential functions is the denominator can be factorized into linear terms. However, if the denominator of this equation cannot be factorized into linear factors, then the response is sinusoidal; because when we take the inverse Laplace transform, we have to complete the square and then we will have an oscillatory term (the sin term). click to see more

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Development of a Bushing Model for Vehicle Durability Simulation

Load and damage analysis on the MotionView shaker share the same concept with that of the MATLAB shaker, by both viewing the load plots and damage indices. The CPG routes for the MotionView shaker are not exactly identical to the MATLAB ones, as the MotionView shaker was tuned separately. An issue with MotionView is that the mass module of the fitted ABM had to be turned off, because of the signal quality difference. Within MATLAB, variables are saved in double precision, and the input displacement can be double differentiated without showing significant numerical distortion. To use the MotionView shaker, the input displacement has be be rewritten into .dac format, which is in single precision. As a standard data transfer format used by MotionView, all variables will be calculated in single precision within the software accordingly, leading to severe distortion shown in double differentiated displacement, i.e., acceleration that will be used by the mass module. The distorted result would greatly alter the damage index. The issue has been reported to Altair for their attention.
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Evaluation of seismo-electric anomalies using magnetic data in Taiwan

the geomagnetic field, specifically among the vertical com- ponent Z, the horizontal component H and the declination D. The complex and frequency-dependent coefficients A and B are computed from HD and Z via the magnetic transferfunction. A and B are dependent on the underlying electri- cal conductivity structure (Lilley and Arora, 1982). Induc- tion arrows (i.e. Parkinson vectors) represent the ratios of the real parts of the eastward B to the northward A. Induc- tion arrows generally point toward source locations, where the strongest induced vertical variations are generated by the inducing horizontal variations (Parkinson, 1962). The mag- nitude of an induction arrow is related to both the proximity of the conductor and its conductivity contrast with the back- ground structure (Hitchman et al., 2000). Thus, the magnetic transferfunction is usually applied to survey sites where the conductivity is higher than in the nearby areas (Parkinson, 1962; Parkinson and Jones, 1979) and it is widely utilised to study time-varying conductivity due to earthquakes (Zeng
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Differences in the Risk Associated With Head Injury for Pediatric Ice Skaters, Roller Skaters, and In-Line Skaters

RESULTS. An estimated ecupid english subtitle for 235 467 pediatric skating participants presented to hospital emergency departments with injuries between 1993 and 2003. These children had a mean age of 10.9 years (SD: 3.2 years; range: 1–18 years), and 50.0% were male. The most common mechanism of injury was a fall (83.1%). Ice skaters sustained a greater proportion of head injuries (13.3%), compared with roller skaters (4.4%) and in-line skaters (5.0%). Ice skaters also experienced a greater proportion of concussions (4.3%), compared with roller skaters (0.6%) and in-line skaters (0.8%). The proportion of facial injuries among ice skaters was greater than the proportions among roller skaters and in-line skaters. The majority of roller skat- ing– and in-line skating–related injuries were upper-extremity fractures (53.9% and 59.7%, respectively). Children ⱕ 6 years of age experienced a greater propor- tion of head and facial injuries than did older children in each skating activity.
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Источник: https://1library.net/subject/head-related-transfer-function

Head-related transfer functions (HRTFs) describe the listener-specific directional filtering of the incoming sound at the entrance of the ear-canal. Since HRTFs are caused by a scattering process, it seems natural to calculate HRTFs numerically by simulating the sound-field scattered by the human head and ear instead of acquiring HRTFs in an acoustical measurement procedure. Modify the 3-D audio image of a sound file by filtering it through a head-related transfer function (HRTF). Set the location of the sound source by specifying the desired azimuth and elevation. load 'ReferenceHRTF.mat' hrtfData sourcePosition hrtfData = permute(double(hrtfData),[2,3,1]); sourcePosition = sourcePosition(:[1,2]);.