The evaluation of human emotions has been a multi-disciplinary area of research interest. Although there are several methods for such evaluation, such as subjective evaluation and behavioral taxonomy, direct evaluation from the human brain is more reliable. Electroencephalograph (EEG) signal analysis is particularly widely used because of its simplicity and convenience. In the present study, human emotional states were investigated using a newly developed EEG device with a single electrode. The developed device is lighter and cheaper than existing devices, although its feasibility is yet to be proven.

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This paper presents an Adaptive Multi-directional Max-plus algebra-based Morphological wavelet Transform (AM-MMT). The AM-MMT is based on a conventional max-plus algebra-based morphological wavelet transform and utilizes several suitable sampling windows that are adaptively selected in accordance with the direction of the content in the image. Thus, this proposed method extracts directional structures smoothly to calculate nonlinear operation (maximum or minimum search) and the standard sum. To show the effectiveness of the AM-MMT, nine standard benchmark images were used to compare the AM-MMT with the conventional MMT. From the experiment, transformed-images can be made by combining the high quality parts of the images, which are processed by each sampling window. All the PSNR values of the AM-MMT are higher than those of the conventional MMT with increasing deletion bit width. Thus, the AM-MMT achieves high-quality high-compression digital images. Furthermore, the expansion into the multi-level AM-MMT operation is described, and a Level 2 (L2) implementation example is shown. The L2 AM-MMT compressed-image is up to about 82% smaller than the original image. Consequently, the AM-MMT can accomplish effective nonlinear operation-based image transformation.

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In this paper, we propose a low complexity group detection using higher order multiple input multiple output (MIMO) decoder. As the MIMO system order increases, a higher order MIMO decoder which achieves a good tradeoff between detection performance and algorithm complexity is demanded. However, there is no higher order MIMO decoder which satisfies the good tradeoff balance. Therefore, we propose a good tradeoff balance using higher order MIMO decoder. In the MIMO wireless LAN multipath environment, the complexity of the proposed algorithm is 14.29 % of the conventional one with only a slight SNR performance degradation. The proposed algorithm is applicable up to 8×8 MIMO decoder.

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Usually, we deal with noise only in output side of a system for a system identification. However, it is known that there are algorithms using an input and output side noise for more appropriate estimation. Then, this paper presents two algorithms of a blind identification for a system in which there are both noises in input and output. The first is based on a simple adaptive gradient method. The second is based on RLS algorithm. When an output noise is added into system, we can achieve more precise estimation of system parameters. Computer simulations show our algorithms' performance.

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The continuous wavelet transform using Gabor wavelet is well known as a high-precision tool for time-frequency analysis. However, its calculation amount is very large, and generally, its practical calculation is discretized depending on experience. In this paper, we consider the discretization method for Gabor wavelet, and propose some approximate tight wavelet frames using Gabor wavelet. In addition, we propose how to thin the wavelets in the continuous wavelet transform using Gabor wavelet and obtained the encouraging results.

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In the steady-state of lossless circuits, resonance can be obtained using the Laplace transform. We focus on commensurate transmission line circuits constructed using eight unit elements as an example and determine the resonance, transient response, and nonstationary response of the circuits using a z-transform. In old quantum theory, light quanta are assumed to satisfy the heat conduction equation. When considering the response of light quanta as a physical phenomenon from the viewpoint of circuit theory, we can interpret that the heat conduction equation describes the propagation of waves on a lossy distributed RC transmission line, in which light quanta repeatedly collide with each other. We demonstrate that light quanta are different from photons, which are interpreted as satisfying the Maxwell's equations and propagating on a lossless transmission line.

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