We proposed a method for constructing constant-weight and multi-valued sequences from the cyclic difference sets by generalization of the method in binary case proposed by N. Li, X. Zeng and L. Hu in 2008. In this paper we give some properties about sets of such sequences and it is shown that a set of non-constant-weight sequences over Z4 with length 13 from the (13,4,1)-cyclic difference set, and a set of constant-weight sequences over Z5 with length 21 from the (21,5,1)-cyclic difference set have almost highest linear complexities and good profiles of all sequences' linear complexities. Moreover we investigate the value distribution, the linear complexity and correlation properties of a set of sequences with length 57 over GF(8) from the (57,8,1)-cyclic difference set. It is pointed out that this set also has good value distributions and almost highest linear complexities in similar to previous two sets over Z4 with length 13 and Z5 with length 21.

For a cyclic code, the BCH Bound and the Hartmann-Tzeng bound are two of well-known lower bounds for its minimum distance. New bounds are proposed by N. Boston in 2001, that depend on defining set of cyclic code. In this paper, we consider the between the Boston bound and these two bounds for non-binary cyclic codes from numerical examples.

The shift bound is a good lower bound of the minimum distance for cyclic codes, Reed-Muller codes and geometric Goppa codes. It is necessary to construct the maximum value of the independent set. However, its computational complexity is very large. In this paper, we consider cyclic codes defined by their defining set, and a new method to calculate the lower bound of the minimum distance using the discrete Fourier transform (DFT) is shown. The computational complexity of this method is compared with the shift bound's one. Moreover construction of independent set is shown.

Most recent work used raw electroencephalograph (EEG) data to train deep learning (DL) models, with the assumption that DL models can learn discriminative features by itself. It is not yet clear what kind of RSVP specific features can be selected and combined with EEG raw data to improve the RSVP classification performance of DL models. In this paper, we tried to extract RSVP specific features and combined them with EEG raw data to capture more spatial and temporal correlations of target or non-target event and improve the EEG-based RSVP target detection performance. We tested on X2 Expertise RSVP dataset to show the experiment results. We conducted detailed performance evaluations among different features and feature combinations with traditional classification models and different CNN models for within-subject and cross-subject test. Compared with state-of-the-art traditional Bagging Tree (BT) and Bayesian Linear Discriminant Analysis (BLDA) classifiers, our proposed combined features with CNN models achieved 1.1% better performance in within-subject test and 2% better performance in cross-subject test. This shed light on the ability for the combined features to be an efficient tool in RSVP target detection with deep learning models and thus improved the performance of RSVP target detection.

For cyclic codes some well-known lower bounds and some decoding methods up to the half of the bounds are suggested. Particularly, the shift bound is a good lower bound of the minimum distance for cyclic codes, Reed-Muller codes and geometric Goppa codes. In this paper we consider cyclic codes defined by their defining set, and new simple derivation of the shift bound using the discrete Fourier transform with unknown elements and the Blahut theorem is shown. Moreover two examples of binary cyclic codes are given.

The Schaub bound is one of well-known lower bounds of the minimum distance for given cyclic code C, and defined as the minimum value, which is a lower bound on rank of matrix corresponding a codeword, in defining sequence for all sub-cyclic codes of given code C. In this paper, we will try to show relationships between the Schaub bound, the Roos bound and the shift bound from numerical experiments. In order to reduce computational time for the Schaub bound, we claim one conjecture, from numerical examples in binary and ternary cases with short code length that the Schaub bound can be set the value from only defining sequence of given code C.

The authors proposed an algorithm for calculation of new lower bound (rank bounded distance) using the discrete Fourier transform in 2010. Afterward, we considered some algorithms to improve the original algorithm with moving the row or column. In this paper, we discuss the calculation method of the rank bounded distance by conjugate elements for cyclic codes.