This study investigates the correspondences between the differences among the phones in human speaker identification and their acoustic properties. In the speaker identification test, the Japanese CV syllables excerpted from the carrier sentences were used as the stimuli. As pointed out in the previous studies, the stimuli containing the nasal sounds were significantly effective for the identification of the speakers, compared to other stimuli containing only the oral sounds. In the acoustic analyses, we analysed the spectral properties of the stimuli in order to explain these differences in the perception test, and we found that the cepstral distances among the speakers were significantly larger in the nasal sounds than in the oral sounds. Also, there were correspondences between the rankings of the consonants in the identification test and in the cepstral distances.

A perceptual discrimination test was conducted to investigate whether humans can discriminate prosodic types solely based on suprasegmental acoustic cues. Excerpts from Chinese, English, Spanish, and Japanese, differing in lexical accent types and rhythm types, were used. From these excerpts, “source” signals of the source-filter model, differing in F0, intensity, and HNR, were created and used in a perceptual experiment. In general, the results indicated that humans can discriminate these prosodic types and that the discrimination is easier if more acoustic information is available. Further, the results showed that languages with similar rhythm types are difficult to discriminate (i.e., Chinese-English, EnglishSpanish, and Spanish-Japanese). As to accent types, tonal/nontonal contrast was easy to detect. We also conducted a preliminary acoustic analysis of the experimental stimuli and found that quick F0 fluctuations in Chinese contribute to the perceptual discrimination of tonal/non-tonal accents.

One of the excitations, 'carrier', is a large signal and an arbitrary T-periodic function of time. The other excitation, 'signal', is considered as a small perturbation to the periodic steady-state response driven by the carrier. To find a small signal frequency response for the 'signal', the method uses variational equations around the periodic steady-state response. These linearized time-varying differential equations are solved in the frequency domain using a time discretization method. The method can be used to compute the small signal frequency responses of nonideal switched capacitor filters, mixers, and other nonlinear circuits, if the circuit has a stable periodic response. The formulation of the problem, computational complexity of the method, error analysis, sensitivity analysis, implementation of the method, and some applications are covered.>

An electronic instrument for displaying any perspective of a three-dimensional surface S generated by three time-varying (not necessarily periodic) signals is described. The surface S is a three-dimensional Lissajous figure which need not be a closed curve as is typical of all strange attractors. This analog (not digital) instrument is designed to rotate S along any axis (not just the X-, Y-, Z-axis) through any prescribed solid angles (0°-360°) in the three-dimensional coordinate system in real time. The instrument works as a preprocessor for a standard oscilloscope and is built with components capable of displaying time-varying signals with a frequency spectrum from 0 to 20 kHz. To illustrate some immediate applications of this instrument, strange attractors associated with both autononmus and nonautonomous circuits are presented in many different perspectives and cross sections. In particular, numerous cross sections of these strange attractors which have never been seen before can be easily displayed in any desired perspective in real time. Such cross sections have proved to be most revealing and invaluable in dissecting and uncovering the fine structures of strange attractors.

The Newton algorithm is one of the most promising methods for determining the steady-state response of nonlinear circuits. However, the method has ever larger memory storage capacity requirements, as the circuit size increases. State elimination is efficient to reduce the required memory storage. In this paper, an automatic state elimination method is proposed. The Newton method has another problem, since it fails to converge to a steady-state solution in certain cases. A damped Newton method, which considers nonlinearity of the system, is discussed as a method to improve convergence. For autonomous systems, such as oscillatory circuits, another modification is discussed for improving reliability and convergence. The Newton algorithm with these modifications has been implemented in Toshiba's version of SPICE2, and experimental results have shown reduction in memory storage capacity requirements, less computational effort and convergence improvements.