Least Number Of Channels Research Articles

Performance uniformity analysis in polymer electrolyte fuel cell using long-term dynamic simulation

The temporal stability and spatial homogeneity of current density are key factors in Polymer Electrolyte Fuel Cell (PEFC) performance and durability. Temporal and spatial variations of relative humidity, fuel concentration, and water droplets in the channels are the principal causes of non-homogeneous current density. A dynamic pseudo-3D model was previously proposed by the authors and has been extended and improved to perform the long-term and intensive simulations of PEFC with low computational cost, which allows to study of the performances homogeneity with different experimental configurations and flow field topologies. The model considers important phenomena in the homogeneity analysis, such as gases and liquid water movement in diffusion layers and flow field, electrochemical reactions, and others. Model validation has been performed using experimental data obtained from a 25 cm2 cell with a single serpentine, which has allowed studying the model transient response and spatial representation. The simulations have been used to study the homogeneity and stability of 36 setups of PEFC, varying the rib/channel width ratio, the stoichiometric ratio, and the number of parallel serpentine channels. The results show the importance of a properly flow field design to control gas flow, remove the channels’ liquid water, and keep a homogeneous feeding. The study evaluated a set of channel configurations that show the improved temporal voltage stability and current density spatial homogeneity. The results show the impact of channel gas speed and ratio channel/rib width in liquid droplets removal and the proper fuel spatial distribution; and how configurations with a lesser number of channels in serpentine design require a lower stoichiometric ratio to perform better temporal and spatial uniformity. In the case of the cell configurations simulated, the optimum design was achieved using between 5 and 7 parallel serpentine channels and a channel/rib ratio 3/5.

A subject-independent portable emotion recognition system using synchrosqueezing wavelet transform maps of EEG signals and ResNet-18

ObjectiveDesigning a portable Brain-Computer Interface (aBCI) using EEG signals is challenging due to the numerous channels, though not all are vital for emotional recognition. We aimed to simplify this by creating a two-channel portable aBCI using advanced time-frequency analysis and deep learning. MethodOur approach involved utilizing the time-frequency analysis named synchrosqueezing wavelet transform (SSWT), which provides better frequency resolution for fluctuations of EEG signal than common wavelet transform. Using the ResNet-18 Convolutional Neural Network, we fine-tuned for sadness and happiness classification. The two best channels were identified across four databases: SEED-IV, SEED-V, SEED-GER, and SEED-FRA, using the Leave-One-Subject-Out method. ResultsFinally, we achieved an average accuracy over sad and happy emotions using the SSWT-ResNet18 model of 76.66%, 78.12%, 81.25%, and 75.00% for the SEED-IV, SEED-V, SEED-GER, and SEED-FRA databases, respectively. ConclusionOverall, our study demonstrates the potential for developing a rapid aBCI by utilizing a precise time–frequency method and deep learning technique from the least number of channels. SignificanceOur approach has promising implications for future real-world applications in emotional recognition.

A novel channel selection method for optimal classification in different motor imagery BCI paradigms.

BackgroundFor sensorimotor rhythms based brain-computer interface (BCI) systems, classification of different motor imageries (MIs) remains a crucial problem. An important aspect is how many scalp electrodes (channels) should be used in order to reach optimal performance classifying motor imaginations. While the previous researches on channel selection mainly focus on MI tasks paradigms without feedback, the present work aims to investigate the optimal channel selection in MI tasks paradigms with real-time feedback (two-class control and four-class control paradigms).MethodsIn the present study, three datasets respectively recorded from MI tasks experiment, two-class control and four-class control experiments were analyzed offline. Multiple frequency-spatial synthesized features were comprehensively extracted from every channel, and a new enhanced method IterRelCen was proposed to perform channel selection. IterRelCen was constructed based on Relief algorithm, but was enhanced from two aspects: change of target sample selection strategy and adoption of the idea of iterative computation, and thus performed more robust in feature selection. Finally, a multiclass support vector machine was applied as the classifier. The least number of channels that yield the best classification accuracy were considered as the optimal channels. One-way ANOVA was employed to test the significance of performance improvement among using optimal channels, all the channels and three typical MI channels (C3, C4, Cz).ResultsThe results show that the proposed method outperformed other channel selection methods by achieving average classification accuracies of 85.2, 94.1, and 83.2 % for the three datasets, respectively. Moreover, the channel selection results reveal that the average numbers of optimal channels were significantly different among the three MI paradigms.ConclusionsIt is demonstrated that IterRelCen has a strong ability for feature selection. In addition, the results have shown that the numbers of optimal channels in the three different motor imagery BCI paradigms are distinct. From a MI task paradigm, to a two-class control paradigm, and to a four-class control paradigm, the number of required channels for optimizing the classification accuracy increased. These findings may provide useful information to optimize EEG based BCI systems, and further improve the performance of noninvasive BCI.

Optimizing the Channel Selection and Classification Accuracy in EEG-Based BCI

Multichannel EEG is generally used in brain-computer interfaces (BCIs), whereby performing EEG channel selection 1) improves BCI performance by removing irrelevant or noisy channels and 2) enhances user convenience from the use of lesser channels. This paper proposes a novel sparse common spatial pattern (SCSP) algorithm for EEG channel selection. The proposed SCSP algorithm is formulated as an optimization problem to select the least number of channels within a constraint of classification accuracy. As such, the proposed approach can be customized to yield the best classification accuracy by removing the noisy and irrelevant channels, or retain the least number of channels without compromising the classification accuracy obtained by using all the channels. The proposed SCSP algorithm is evaluated using two motor imagery datasets, one with a moderate number of channels and another with a large number of channels. In both datasets, the proposed SCSP channel selection significantly reduced the number of channels, and outperformed existing channel selection methods based on Fisher criterion, mutual information, support vector machine, common spatial pattern, and regularized common spatial pattern in classification accuracy. The proposed SCSP algorithm also yielded an average improvement of 10% in classification accuracy compared to the use of three channels (C3, C4, and Cz).

Down-mixing of multi-channel audio for sound field reproduction based on spatial covariance

This article describes a method for automatic down-mixing multi-channel audio content on the basis of spatial covariance. Such a down-mixing method should be able to convert the signal of the original multi-channel audio system into that for an alternative system with the lesser number of channels, while maintaining the spatial impression of sound. Moreover, it should take into account the listener’s position and transfer function. Wave surface control and convolving the head related transfer function are techniques used in sound field control or reproduction. We consider that the spatial impressions of a sound field, which we perceive through our ears, are reproduced by preserving the relative relationship between observation points even if the wave surface is not completely controlled. Takahashi et al. proposed a new sound field reproduction method that we named “SOund field Reproduction based on sPAtial Covariance” (SORPAC). SORPAC can control the point-to-point covariance in a sound field. We expect that this sound field reproduction method based on spatial covariance can be applied to down-mixing of multi-channel content because SORPAC does not require the listener’s position or transfer function. This article describes SORPAC and its characteristics. We used SORPAC for down-mixing audio content. We confirmed that SORPAC-based down-mixing could accurately reproduce the interaural cross correlation (IACC) in relation to the listener’s position.

Maximum scan statistics and channel assignment problems in homogeneous wireless networks

In wireless networks, to avoid collisions of simultaneous transmissions over the same channel, adjacent nodes are assigned distinct channels, and the least number of channels used in an assignment is called the chromatic number. The determination of the chromatic number is NP-hard. In this paper, we introduce an analytic tool called maximum scan statistics. For a finite point set V and a convex compact set C , the maximum scan statistic of V with respect to the scanning set C is the largest number of points in V covered by a copy C . Based on the study of asymptotic maximum scan statistics, we obtain the asymptotics of the maximum degree and the clique number of homogeneous wireless networks. The results imply that the chromatic number is almost surely at most four times the clique number. We further prove that the approximation ratios of some vertex-ordering-based First-Fit channel assignment algorithms are almost surely bounded by 2. In the analysis, we also learn that the chromatic number is almost surely at most twice the clique number.

Surround sound channel encoding and decoding

Surround sound encoding and decoding includes apparatus and techniques for encoding a number of major channels of a surround sound signal, such as left, right, center, left surround and right surround, into a lesser number of channels, such as left transmitted and right transmitted, and decoding the lesser number of channels into a larger number of decoded channels, such as left, right, center, left surround and right surround, for being electroacoustically transduced.

The Stereophonic Sound-Film System—General Theory

The general requirements are discussed for an ideal recording-reproducing system as determined by the characteristics of hearing of a typical group of persons listening in a typical concert hall or theater. Quantitative values are set down as ideal objectives. Although microphones, loud speakers, and amplifiers which had been developed for the stereophonic transmission system were available for meeting these objectives, no recording medium was known which would record the wide dynamic range of intensity levels which the objectives indicated was necessary. However, this wide intensity range objective was met by using a compandor in the electrical system. A general discussion is given of the reasons for choosing the particular compandor used, for using variable-area rather than variable-density on the recorded film, for using three instead of a greater or lesser number of channels. A general description of the stereophonic sound-film system is given, including the enhancement feature. This feature makes it possible to re-record from the original recording, at the same time making any desirable changes in the dynamic range or frequency response in each of the three channels.

General Theory

The general requirements are discussed for an ideal recording-reproducing system as determined by the characteristics of hearing of a typical group of persons listening in a typical concert hall or theater. Quantitative values are set down as ideal objectives. Although microphones, loudspeakers and amplifiers which had been developed for the stereophonic transmission system were available for meeting these objectives, no recording medium was known which would record the wide dynamic range of intensity levels which the objectives indicated was necessary. However, this wide intensity range objective was met by using a compandor in the electrical system. A general discussion is given of the reasons for choosing the particular compandor used, for using variable area rather than variable density on the recorded film, for using three instead of a greater or lesser number of channels. A general description of the stereophonic sound film system is given, including the enhancement feature. This feature makes it possible to re-record from the original recording, at the same time making any desirable changes in the dynamic range or frequency response in each of the three channels.