In this paper, two partial transmit sequence (PTS) schemes without side information (SI) are proposed for reducing peak-to-average power ratio of orthogonal frequency division multiplexing signals. The proposed schemes do not transmit SI identifying a rotating vector because identifiable phase offset is applied to the elements of each rotating vector. To extract SI from the received signal and recover the data sequence, the maximum likelihood (ML) detector is used. This ML detector exploits the Euclidean distance between the given signal constellation and the signal constellation rotated by the phase offset. By doing pairwise error probability (PEP) analysis, it is investigated how to choose good phase offsets for embedding SI. Also, the performance degradation caused by SI detection failure is analyzed based on PEP. Finally, through numerical analysis, it is shown that the BER performance of the proposed PTS schemes is not degraded compared with the conventional PTS with perfect SI.

Fuzzy graphs are the backbone of many real systems like networks, image, scheduling, etc. But, due to some restriction on edges, fuzzy graphs are limited to represent for some systems. Generalized fuzzy graphs are appropriate to avoid such restrictions. In this study generalized fuzzy graphs are introduced. In this study, matrix representation of generalized fuzzy graphs is described. Completeness and regularity are two important parameters of graph theory. Here, regular and complete generalized fuzzy graphs are introduced. Some properties of them are discussed. After that, effective regular graphs are exemplified.

In this letter, a blind reconstruction method of Bose-Chaudhuri-Hocquenghem (BCH) codes is proposed, which uses the property that all the codeword polynomials of a t-error correcting BCH code have the same 2t consecutive roots over Galois field. The proposed method inherently eliminates most of the erroneous codewords from the received codewords by utilizing the information about the starting position and length of consecutive roots of each received codeword. Therefore, the blind reconstruction performance is substantially improved and the simulation results confirm that the proposed method outperforms other blind reconstruction methods.

Partial transmit sequence (PTS) is a probabilistic peak-to-average power ratio (PAPR) reduction scheme for orthogonal frequency division multiplexing (OFDM) signals, but it requires an exhaustive search for the one with the minimum PAPR over all alternative OFDM signal vectors. In order to reduce such computational complexity, it was proposed that the PAPR value of each alternative OFDM signal vector is approximately estimated by using dominant time-domain samples selected based on a simple metric. In this paper, two new effective metrics for selecting dominant time-domain samples are proposed for low-complexity PTS scheme. For further lowering the computational complexity, two low-complexity PTS schemes are proposed by sorting the dominant time-domain samples in decreasing order of their metric values. Simulation results confirm that compared with the conventional PTS scheme, the proposed PTS schemes show identical PAPR reduction performance with substantially reduced computational complexity.

Partial transmit sequence (PTS), a well‐known peak‐to‐average power ratio (PAPR) reduction scheme for orthogonal frequency division multiplexing (OFDM) systems, has been actively investigated to reduce its high computational complexity. Ku et al . proposed a selection method of dominant time‐domain samples and by only using the selected samples, the PAPR of each alternative OFDM signal vector is calculated. This method clearly reduces the computational complexity but it is crucial to select proper time‐domain samples to achieve acceptable PAPR reduction performance. In this study, a new selection method of dominant time‐domain samples is proposed based on rotating samples of inverse fast Fourier transformed (IFFTed) subblocks to the local area on which the corresponding sample of the IFFTed first subblock is located. Moreover, pre‐exclusion of phase rotating vectors based on the above time‐domain sample rotation is proposed to further reduce the computational complexity. Numerical results confirm that the proposed PTS schemes substantially reduce the computational complexity with negligible degradation of PAPR reduction performance.

Modelling complex systems poses significant challenges on how one represents the system components and interactions among them. In order to provide a systematic approach to represent human participation as a part of a dynamic system, this paper presents a formal automata model of human-machine cooperative systems that incorporates human capabilities with respect to system conditions. Specifically, we propose a control model for human-involved shop floor systems based on discrete event-based systems (DES) and an environmental concept known as an affordance. When modelling human-involved systems where a human operator is considered a crucial system component, it is necessary to analyse the model complexity that increases significantly due to a human's behavioural patterns. From the perspective of the temporal and physical state domains a human operator's behaviour is usually limited by attention and resource constraints. We investigate these limitations and map them into constrained system affordances, and then construct a formal human-machine cooperative model based on the finite state automaton (FSA) model. The proposed model can provide a framework to combine human activities into systems operations in consideration of human's effectivities and system affordances. A detailed application example is provided to illustrate that the proposed model can effectively be applied to manufacturing control systems.