PUFs, that self-generate random numbers, are used in identification or authentication applications for two reasons: cost and security. Since the randomness of PUFs in individual chips may differ, PUFs in some chips may generate somewhat less than random values. Defects during manufacturing may also affect the randomness of PUFs. In either case, confidential information based on PUFs could be vulnerable to security threats. Thus, it is necessary to identify both failing chips during manufacturing and PUFs which are not sufficiently random. To test the randomness of PUFs in a chip, we have designed a dedicated random test module optimized for hardware implementation. Finally, by implementing the module in real PUFs, we verified its validity.

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This paper presents an overview of some recent approaches to modeling communication systems with a focus on dynamical effects. The paper focuses on models of communication between agents using multiple layers of protocols, with examples practical scenarios in wireless Peer-to-Peer communications. The first topic is analysis of behavior space and nonlinear relations between system parameters as a framework for understanding complex behavior. The second topic is microsimulation of communication protocols as multi-layer automata models. The third topic is stochastic models of protocols that reduce computational complexity and make it easier to analyze large systems.

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We have introduced the induced transformations associated with the interval algorithm. In view of the entropy of the induced transformations, the stopping time of the algorithm is evaluated. Sharp upper and lower bounds on the mean value of the stopping time are given for the case that the source and the target have uniform distributions. We generalize these bounds to the case that the source and the target have arbitrary distributions whose elements are all rational numbers.

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Ensuring security at the physical layer in wireless communications is important and effective because it can omit upper-layer secure protocols in ad hoc or multi-hop relay transmissions, or it can enhance security together with upper-layer protocols. To realize this system, we have proposed a chaos-based multiple-input multiple-output (MIMO) transmission scheme that enables both physical-layer security and a channel coding effect in a MIMO multiplexing transmission. However, the transmission rate is equivalent to binary phase shift keying (BPSK), that is, one bit/symbol, and multilevel modulations are needed to achieve higher-capacity communication. Moreover, the channel coding gain is limited, which needs to be improved. Therefore, in this paper, we propose a two- and four-bit/symbol chaos-MIMO scheme, equivalent to quadrature phase shift keying (QPSK) and 16 quadrature amplitude modulation (16QAM) rate-efficiency, with an adaptive chaos processing scheme enhancing the channel coding gain. The improved performances of the proposed scheme are shown in the numerical results. In addition, we describe the concept of identification modulation using this chaos transmission.

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Nonlinear oscillators driven by correlated noisy signals can synchronize without direct mutual interactions. Here we show that correlation between noisy signals can be enhanced by applying a threshold filter, and the filtered signals can be used to improve noise-induced synchronization. We derive analytical expressions for the correlation coefficient between the filtered signals, and, using simple examples, we demonstrate that the correlation can actually be enhanced and the synchronization can be improved by the threshold filtering in some cases.

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Wireless multihop networks can be potentially used to realize a smart community that comprehensively controls social infrastructures. In a wireless multihop transmission, personal data are forwarded by a third party, so wireless security is indispensable. In current wireless systems, security is ensured by encryption in the upper layers. However, this encryption tends to require a complex protocol or processing, which is not suitable for a multihop protocol with a simple implementation. To solve this problem, we have proposed a chaos multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) scheme with physical layer encryption and channel-coding abilities. On the other hand, an effective technique for wireless multihop transmission is point-to-multipoint (P-MP) communication, and recently, multi-user (MU)-MIMO has been proposed as an effective P-MP scheme. In MU-MIMO, wireless security is also important. However, there are few studies considering MU-MIMO security in the physical layer. Therefore, in this paper, we propose a multiuser (MU) chaos MIMO-OFDM scheme that achieves physical layer security and channel-coding gain in MU-MIMO transmission. Additionally, the user distribution and propagation loss are taken into consideration. The improved performances are shown through computer simulations.

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In this paper, a novel approach, WPLSSVM, has been proposed for electricity demand forecasting, which combines particle swarm optimization (PSO), least squares support vector machine (LSSVM), and wavelet transform (WT). Firstly, the wavelet transform method is used to decompose the original sequence in WPLSSVM. Secondly, the WPLSSVM models the series using LSSVM, in which the parameters have been optimized by particle swarm optimization. Lastly, WPLSSVM obtains the final prediction by wavelet reconstruction. To test the model, the half-hour electricity demand series of New South Wales (NSW) in Australia has been used. The results demonstrate the validity of the approach.

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The “tug-of-war (TOW) model” is a unique parallel search algorithm for solving the multi-armed bandit problem (BP), which was inspired by the photoavoidance behavior of a single-celled amoeboid organism, the true slime mold Physarum polycephalum [1-4]. “The cognitive medium access (CMA) problem,” which refers to multiuser channel allocations of the cognitive radio, can be interpreted as a “competitive multi-armed bandit problem (CBP) [5, 6].” Unlike the normal BP, the CBP considers a competitive situation in which more than one user selects a channel whose reward probability (probability of which channel is free) varies depending on the number and combination of the selecting users as indicated in a payoff matrix. Depending on the payoff matrix, the CBP provides a hard problem instance in which the users should not be attracted to the Nash equilibrium to achieve the “social maximum,” which is the most desirable state to obtain the maximum total score (throughput) for all the users. In this study, we propose two variants of the TOW model (solid type and liquid type) for the CBP toward developing a CMA protocol using a distributed control in uncertain environments. Using the minimum CBP cases where both the users choose a channel from the two considered channels, we show that the performance of our solid-type TOW model is better than that of the well-known upper confidence bound 1 (UCB1)-tuned algorithm, particularly for the hard problem instances. The aim of this study is to explore how the users can achieve the social maximum in a decentralized manner. We also show that our liquid-type TOW model, which introduces direct interactions among the users for avoiding mutual collisions, makes it possible to achieve the social maximum for general CBP instances.

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The present paper proposes a novel M-ary modulation scheme based on separation and reconstruction of deterministic chaotic dynamics for noncoherent chaos-based communications. The M-ary modulation scheme can transmit b-bit data at a time by using M=2^b distinct sequences. In order to generate M distinct sequences and recover b-bit data, the proposed system separates the chaotic dynamics having the chaotic sequence by using M interleavers, and reconstructs the original sequence based on the chaotic dynamics from the separated one by using M deinterleavers. In advance, each data symbol among M symbols is allocated to each interleaver-deinterleaver pair. The transmitter selects an interleaver corresponding to a data symbol and separates the order of samples of the chaotic sequence using the selected interleaver. The receiver feeds the received sequence into all M deinterleavers and outputs M reconstructed sequences. The proposed system can reconstruct the original chaotic sequence only when the correct deinterleaver, which becomes paired with the interleaver, is selected. Therefore, the receiver can recover b-bit data by analyzing the chaotic dynamics of each reconstructed sequence. We carry out computer simulations and evaluate performances of the proposed M-ary modulation scheme.

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Multidirectional associative memory (MAM) enables associations among many items. Its architecture is very simple and provides high parallelism. However, recall results of MAMs are inconsistent for contradictory inputs. The recall results depend on the order of update. If a given input includes an incorrect pattern, we expect that the incorrect pattern will be corrected, and the recalled pattern is determined by the majority. In this work, we propose MAMs with self-connections and a new learning algorithm. These MAMs provide recall results independent of the order of update. Furthermore, they maintain the advantages of MAMs, such as their simple architecture, high parallelism and stability.

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We partially solve a fundamental problem posed by Fredricksen on existence of CR (complement reverse) sequences in the de Bruijn sequences of length 2^2p+1(p≥1). For the case that p is a prime number, we construct the set of CR graphs, which yields all CR sequences. As an application of this result, we discuss enumeration of the total number of distinct auto-correlation functions for the set of de Bruijn sequences of length 2^2p+1. Since the worst cases of the normalized cross-correlation functions for pairs of de Bruijn sequences are characterized by the normalized auto-correlation functions for sequences of the worst pairs, we obtain upper bounds of the total number of distinct auto-correlation functions for the set of de Bruijn sequences of length 2ⁿ(n≥4).

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