Perception of temporal patterns defined by tonal sequences

This experiment tested how listeners discriminate between the temporal patterns defined by two sequences of tones. Two arrhythmic sequences of n tones were played successively (n = 8, 12, or 16, tone duration = 35 ms, frequency = 1000 Hz), and the listener reported whether the sequences had the same or different temporal patterns. In the first sequence, the durations of the intertone gaps were chosen at random; in the second sequence, the gaps were either (a) the same as the first sequence or (b) chosen at random. Discrimination performance increased with the variability of the gap sequences and decreased with the size of the correlation between the sequences. A discrimination model based on computation of the sample correlation between the sequences of gaps, but limited by an internal variability of approximately 15 ms, described observer performance in a variety of conditions.     

Generation of hierarchically correlated multivariate symbolic sequences

We introduce a method to generate multivariate series of symbols from a finite alphabet with a given hierarchical structure of similarities based on the Hamming distance. The target hierarchical structure of similarities is arbitrary, for instance the one obtained by some hierarchical clustering method applied to an empirical matrix of similarities. The method that we present here is based on a generating mechanism that does not make use of mutation rate, which is widely used in phylogenetic analysis. Here we use the proposed simulation method to investigate the relationship between the bootstrap value associated with a node of a phylogeny and the probability of finding that node in the true phylogeny. The results of this analysis are compared with those obtained in the literature according to an evolutionary model with a per-symbol constant mutation rate. We observe that the relationship between the bootstrap value of a node and the probability of the corresponding clade being correct is sensitive to both the length of data series and the length of the branch connecting the node to its closest ancestor in the phylogenetic tree, whereas such a relationship is only slightly affected by the topology of the true phylogeny and by the absolute value of similarity.     

Missing ordinal patterns in correlated noises

Recent research aiming at the distinction between deterministic or stochastic behavior in observational time series has looked into the properties of the “ordinal patterns” [C. Bandt, B. Pompe, Phys. Rev. Lett. 88 (2002) 174102]. In particular, new insight has been obtained considering the emergence of the so-called “forbidden ordinal patterns” [J.M. Amigó, S. Zambrano, M.A. F Sanjuán, Europhys. Lett. 79 (2007) 50001]. It was shown that deterministic one-dimensional maps always have forbidden ordinal patterns, in contrast with time series generated by an unconstrained stochastic process in which all the patterns appear with probability one. Techniques based on the comparison of this property in an observational time series and in white Gaussian noise were implemented. However, the comparison with correlated stochastic processes was not considered. In this paper we used the concept of “missing ordinal patterns” to study their decay rate as a function of the time series length in three stochastic processes with different degrees of correlation: fractional Brownian motion, fractional Gaussian noise and, noises with f^−k power spectrum. We show that the decay rate of “missing ordinal patterns” in these processes depend on their correlation structures. We finally discuss the implications of the present results for the use of these properties as a tool for distinguishing deterministic from stochastic processes.     

Emergence of temporal regimes in fire sequences

Temporal regimes in fire data recorded from 1997 to 2003 in an area of central Italy have been detected by using the Allan Factor statistics. Our findings reveal the presence of meteo-climatic-related periodicities; furthermore time-scaling behaviour characterizes the point process of the fire sequence as a fractal process with a high degree of time-clusterization of the events.     

Aging and temporal discrimination in auditory sequences.

This study examined age-related changes in temporal sensitivity to increments in the inter-onset intervals (IOI) of successive components in tonal sequences. Temporal discrimination was examined using reference stimulus patterns consisting of five 50-ms, 4000-Hz components with equal tonal IOIs selected from the range 100-600 ms. Discrimination was examined in separate conditions by measuring the relative difference limen (DL) for increments of tonal IOI in comparison sequences. In some conditions, comparison sequences featured equal increments of all tonal lOIs to examined listener sensitivity to uniform changes of sequence rate, or tempo. Other conditions measured the DL for increments of a single target IOI within otherwise uniform-rate comparison sequences. For these measurements, the single target IOI was either fixed in sequence location, or randomized in location across listening trials. Listeners in the study included four groups of young and elderly adults with and without high-frequency hearing loss. The results for all listeners showed the relative DL for rate discrimination to decrease from a maximum at the 100-ms IOI to a smaller stable value across the range of longer sequence IOI. All listeners also exhibited larger relative DLs for discrimination of single target intervals compared to rate discrimination for equivalent reference IOI values. Older listeners showed poorer performance than younger listeners in all conditions, with the largest age differences observed for discrimination of brief single intervals that were varied randomly in sequence location. None of the results revealed significant effects of hearing loss on performance of younger and older listeners.     

Neural responses to auditory temporal patterns

Sets of regularly repeating auditory stimuli elicit unique perceptions; listeners are able to identify specific temporal patterns. Some temporal patterns are unambiguous (only one pattern can be perceived), while others are ambiguous (numerous patterns can be detected). While the psychophysical properties of such percepts have been well studied, little is known about the underlying neurological bases of temporal pattern perception. In this experiment, the role of adaptation in temporal pattern perception is examined by studying neural responses in four cats to a temporal pattern that is perceptually unambiguous and one that is perceptually ambiguous. Measurements were made of the whole-nerve action potential, the auditory brainstem response, and potentials from the surface of the primary auditory cortex. The adaptation patterns corresponded with the perceptual organization of temporal patterns in humans at all levels of the nervous system studied.     

Scaling properties in temporal patterns of schizophrenia

Investigations into the patterns of schizophrenia reveal evidence of scaling properties in temporal behaviour. This is shown in the spectral properties of mid-range and long-range (up to two years) daily recordings from a sample of patients drawn at the therapeutic dwelling SOTERIA (Ambühl et al., in: Springer Series in Synergetics, Vol. 58, eds. Tschacher et al. (Springer, Berlin, 1992) pp. 195–203 and references therein) of the Psychiatric University Hospital in Bern. The therapeutic setting is unique in that it tries to avoid treatment by medication.

Power law behaviour has been found within fractal walk analysis and Fourier spectra for the daily fluctuations. A simple dynamic principle, based on a generic intermittency model, is put in relation to these time series thus predicting an additional scaling law for the distribution P(T) of time spans T between successive hospitalizations. Testing this hypothesis with our data shows only insignificant deviations. A possible role of this dynamic principle in the risk assignment of psychotic phases is explored with the help of an example.     

Emergence of spatio-temporal patterns in forest-fire sequences

Temporal variation of spatial clustering in fire data recorded from 1997 to 2003 in Tuscany region, central Italy, has been investigated using the Voronoï polygon area, the Morishita index and the fractal dimension. Our findings reveal that the spatial clustering of fire events changes with time, showing an enhancement of the clustering degree before the largest events.     

Evolution of network structure by temporal learning

We study the effect of learning dynamics on network topology. A network of discrete dynamical systems is considered for this purpose and the coupling strengths are made to evolve according to a temporal learning rule that is based on the paradigm of spike-time-dependent plasticity. This incorporates necessary competition between different edges. The final network we obtain is robust and has a broad degree distribution.     

Spectral and temporal cues for phoneme recognition in noise

Cochlear implant users receive limited spectral and temporal information. Their speech recognition deteriorates dramatically in noise. The aim of the present study was to determine the relative contributions of spectral and temporal cues to speech recognition in noise. Spectral information was manipulated by varying the number of channels from 2 to 32 in a noise-excited vocoder. Temporal information was manipulated by varying the low-pass cutoff frequency of the envelope extractor from 1 to 512 Hz. Ten normal-hearing, native speakers of English participated in tests of phoneme recognition using vocoder processed consonants and vowels under three conditions (quiet, and +6 and 0 dB signal-to-noise ratios). The number of channels required for vowel-recognition performance to plateau increased from 12 in quiet to 16-24 in the two noise conditions. However, for consonant recognition, no further improvement in performance was evident when the number of channels was > or =12 in any of the three conditions. The contribution of temporal cues for phoneme recognition showed a similar pattern in both quiet and noise conditions. Similar to the quiet conditions, there was a trade-off between temporal and spectral cues for phoneme recognition in noise.     

基于流形学习的极端学习机及其在人脸识别中的应用

极端学习机以其快速高效和良好的泛化能力在模式识别领域得到了广泛应用,然而现有的ELM及其改进算法并没有充分考虑到数据维数对ELM分类性能和泛化能力的影响,当数据维数过高时包含的冗余属性及噪音点势必降低ELM的泛化能力,针对这一问题本文提出一种基于流形学习的极端学习机,该算法结合维数约减技术有效消除数据冗余属性及噪声对ELM分类性能的影响,为验证所提方法的有效性,实验使用普遍应用的图像数据,实验结果表明本文所提算法能够显著提高ELM的泛化性能。     

Relative contributions of spectral and temporal cues for phoneme recognition

Cochlear implants provide users with limited spectral and temporal information. In this study, the amount of spectral and temporal information was systematically varied through simulations of cochlear implant processors using a noise-excited vocoder. Spectral information was controlled by varying the number of channels between 1 and 16, and temporal information was controlled by varying the lowpass cutoff frequencies of the envelope extractors from 1 to 512 Hz. Consonants and vowels processed using those conditions were presented to seven normal-hearing native-English-speaking listeners for identification. The results demonstrated that both spectral and temporal cues were important for consonant and vowel recognition with the spectral cues having a greater effect than the temporal cues for the ranges of numbers of channels and lowpass cutoff frequencies tested. The lowpass cutoff for asymptotic performance in consonant and vowel recognition was 16 and 4 Hz, respectively. The number of channels at which performance plateaued for consonants and vowels was 8 and 12, respectively. Within the above-mentioned ranges of lowpass cutoff frequency and number of channels, the temporal and spectral cues showed a tradeoff for phoneme recognition. Information transfer analyses showed different relative contributions of spectral and temporal cues in the perception of various phonetic/acoustic features.     

Holographic character recognition using weighted patterns

As the method of improving the discrimination in character recognition using holographic spatial filtering, this paper proposes a pattern weighting technique which emphasizes differences between characters. Its merit is in the capability of optimally setting the correlations which leads to the feasibility of discrimination. By using weighted patterns obtained by computer calculations, its effectiveness is experimentally proved.     

Speaker recognition with temporal cues in acoustic and electric hearing

Natural spoken language processing includes not only speech recognition but also identification of the speaker's gender, age, emotional, and social status. Our purpose in this study is to evaluate whether temporal cues are sufficient to support both speech and speaker recognition. Ten cochlear-implant and six normal-hearing subjects were presented with vowel tokens spoken by three men, three women, two boys, and two girls. In one condition, the subject was asked to recognize the vowel. In the other condition, the subject was asked to identify the speaker. Extensive training was provided for the speaker recognition task. Normal-hearing subjects achieved nearly perfect performance in both tasks. Cochlear-implant subjects achieved good performance in vowel recognition but poor performance in speaker recognition. The level of the cochlear implant performance was functionally equivalent to normal performance with eight spectral bands for vowel recognition but only to one band for speaker recognition. These results show a disassociation between speech and speaker recognition with primarily temporal cues, highlighting the limitation of current speech processing strategies in cochlear implants. Several methods, including explicit encoding of fundamental frequency and frequency modulation, are proposed to improve speaker recognition for current cochlear implant users.