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EN
A practical identification method of functional type for sound insulation systems is derived especially in the form matched to the prediction problem of output response probability distribution once after introducing some new evaluation criteria on output statistics. The probability distribution of output response with an arbitrary input sound under the contamination of background noise is principally able to predict theoretically by positively using the statistics of input and background noises based on the physical law of intensity linearity. More specifically, the system parameters of the objective sound insulation system are systematically identified by employing an equivalence property between the experimentally observed output probability distribution and the theoretically predicted one as a criterion of the parameter identification. As an application to the actual noise environment, the proposed method has been concretely applied to a double walls sound insulation system and experimentally confirmed under a music sound input.
EN
Since the non-stationary fluctuation of actual acoustic environment like the road traffic noise within a long time interval is usually caused not by the change of merely additional external noise but by the essential change of internal factors themselves, it is reasonable to give as a mathematical model of this non-stationary fluctuation not an additive model but a multiplicative model. In this paper, mainly from a methodological viewpoint, first, the characteristic function method of Mellin transform type for the above multiplicative model is introduced and a new unified expression form of the probability density function within a long time interval is derived in an expansion form based on the probability density function within a short time interval of local stationary type as its first expansion term with distribution parameters reflecting hierarchically various types linear and nonlinear correlation information.
EN
A non-stationary environmental noise fluctuations can be treated as some composition of local state strips having arbitrary fluctuating pattern in a locally stationary time period. Its non-stationary characteristics can be seen in the form of its changing stage from a locally stationary state to another one by means of its temporal change of probability distribution. For a non-stationarity with continuously slow temporal change, the noise evaluation method is derived by considering the temporal change of moment statistics or distribution parameters. On the other hand, for a non-stationarity with stepwise rapid variation like an ON/OFF operation of machine, the noise evaluation method is derived by considering in principle the occurring probability of each of locally stationary state based on the mutually exclusive property. In the experimental consideration, the above contrastive two evaluation methods have been applied to actual cases with slowly changing environmental noise and rapidly changing machine noise.
EN
In the actual situation of measuring an environmental noise, it is very often that only the resultant stochastic fluctuation contaminated by an additional noise of arbitrary distribution type can be observed. In this paper at first a noise cancellation for reasonably removing the effect of the above additional noise, especially in a whole probability distribution form, is derived theoretically in order to estimate only the undisturbed objective output response. Next, for the purpose of predicting a whole expression form of the output response probability of an acoustic system excited by an arbitrary stochastic input with the additional noise, a new stochastic signal processing method, reflecting the effect of the additional noise fluctuation, is proposed in a whole probability distribution form. The effectiveness of the proposed theoretical methods is experimentally confirmed too by applying them to the actual data measured in the complicated sound wall systems.
EN
Nowadays, owing to the rapid and wide application of many type information technology equipments, we are always exposed to acoustic and electromagnetic waves. For evaluating step by step these complicated accumulative and multiplicative effects, it is first important to extract the correlation information among them as deeply and quantatively as possible. In this paper, some new trial of hierarchically evaluating mutual correlation between them is proposed based on the conditional probability density function form derived from a statistical type Hermite series expansion expression for the two-variate joint probability density function. The proposed method has been experimentally confirmed by applying it to the actual environment around~VDT.
EN
For the purpose of decreasing an impact sound level in the room below in a house, a new fundamental study on the impact sound of floors is given in the case of a wood joist floor above the structural concrete slab. In Japan, we have so many opportunities to use wood joist floors in housing. The wood joist floor is convenient and suitable for our Japanese life style. From such a practical viewpoint, a wood joist floor above the reinforced dense concrete floor is considered. Especially a new theoretical trial based on the introduction of equivalent concentrated constant circuit models of electric and mechanical types for an impact noise transmission of a wood joist floor is proposed first. Thus, a practical evaluation of the impact noise reduction can be theoretically estimated by the model method proposed. In the case of a wood joist floor using a resilient material under the wood joist, a quantitative improvement in the impact noise reduction has been systematically expected. Then, from an experimental viewpoint, we have succeeded in confirming the validity of our theory, especially in the case of the I.S.O. standard tapping machine. As a result, we have found a fairly good agreement between our theory and the principle experiment.
7
Content available remote A note on identifying a transmission factor in room acoustics
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EN
In this study, as a concrete example of the non-linear inverse problem in indoor sound fields, a complex sound fluctuation leaked through an aperture gap in the partition door of a coupled room under the actual sound environment has been discussed. A probability evaluation theory introducing a simple stochastic inverse system model has been proposed first especially from an object-oriented viewpoint. More concretely, in order to evaluate the output response probability distribution of the acoustic intensity in the sound receiving room, after introducing time-averaged stochastic variables, we have identified functionally the leakage property as some variability of a transmission factor. Then, we have predicted the output response probability distribution for a new arbitrary stochastic input once after establishing a prediction theory for the probability distribution of a multiplicative model. Finally, an effectiveness of the proposed theory has been experimentally confirmed too by an application to actual indoor sound field data.
EN
In a usual modeling method for actual stochastic systems, it is very often to find some idealized model by paying attention to only the average form of stochastic phenomena. Namely, the deviations form this idealized model are artificially treated as some meaningless information. Especially in a case when considering an arbitrary non-linear system with non-Gaussian input signals, however, the available informations still remain in these deviations in order to estimate and predict precisely some stochastic characteristics, e.g., the probability density function (abbr., p.d.f.), the cumulative distribution function (abbr., c.d.f.) and the higher order non-linear correlation functions. In the usual modeling methods for actual systems, the deviations from the actual phenomena occur inevitably owing to the model constructions under the idealized conditions.
EN
Combinatorial optimization problems compose an important class of matliematical problems that include a variety of practical applications, such as VLSI design automation, communication network design and control, job scheduling, games, and genome informatics. These problems usually have a large number of variables to be solved. For example, problems for VLSI design automation require several million variables. Besides, thieir computational complexity is often intractable due to NP-hardness. Neural networks have provided elegant solutions as approximation algorithms to these hard problems due to their natural parallelism and their affinity to hardware realization. Particularly, binary neural networks have great potential to conform to current digital VLSI design technology, because any state and parameter in binary neural networks are expressed in a discrete fashion. This paper presents our studies on binary neural networks to the N-queens problem, and the three different approaches to VLSI implementations focusing on the efficient realization of the synaptic connection networks. Reconfigurable devices such as CPLDs and FPGAs contribute the realization of a scalable architecture with the ultra high speed of computation. Based on the proposed architecture, more than several thousands of binary neurons can be realized on one FPGA chip.
EN
Work ability is partly determined by physical and mental fitness. Bench step exercise can be practiced anywhere at any time. The aim of this study was to determine the effects of a bench step exercise on work ability by examining cardiovascular risk factors and oxidative stress. Thirteen volunteers working in a warehousing industry comprised the bench step exercise group (n = 7) and the control group (n = 6). The participants in the step exercise group were encouraged to practice the step exercise at home for 16 weeks. The step exercise improved glucose metabolism and antioxidative capacity and increased work ability by reducing absences from work and improving the prognosis of work ability. The improvement in work ability was related to a reduction in oxidative stress. These results suggest that a bench step exercise may improve work ability by reducing cardiovascular risk factors and oxidative stress.
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