This paper provides an overview on the recent research on networked control with an emphasis on the tight relation between the two fields of control and communication. In particular, we present several results focusing on data rate constraints in networked control systems, which can be modeled as quantization of control-related signals. The motivation is to reduce the amount of data rate as much as possible in obtaining control objectives such as stabilization and control performance under certain measures. We also discuss some approaches towards control problems based on techniques from signal processing and information theory.

In this paper, for networked systems, synthesis of self-triggered controllers is addressed. In the proposed method, the control input and the sampling time such that a given cost function is minimized are computed simultaneously. First, the optimal control problem of continuous-time linear systems is rewritten as that of systems with integral continuous-time dynamics. Next, this problem is approximately reduced to a linear programming problem. The proposed method can be applied to model predictive control. Finally, the effectiveness of the proposed method is shown by a numerical example.

This paper discusses a wireless control system for cooperative motion of multiple machines, and clarifies the influence of packet losses on the system behavior. We focus on the synchronization of the motion of the machines, and using the nature of wireless, we propose a new wireless control scheme for maintaining the synchronization performance under packet loss conditions. In the proposed scheme, each controlled object (plant) utilizes control information destined for all plants, and the main controller also utilizes state information of all plants. The additional information of the other controller-plant pairs is used to compensate lost information. As an example of the controlled plants, rotary inverted pendulums, which move synchronously with wireless connections in their control-feedback loops, are considered. Numerical examples confirm the superiority of the proposed scheme from the view-point of the synchronization of the motion of the plants.

This paper discusses a control system that employs a power line to transfer signals to control the motion of a single machine, and explores the influence of packet losses on the quality of the control. As an example of a controlled system, a controller with a rotary inverted pendulum as a controlled object, is considered. The feedback loop in between is the power line. The control performance is evaluated in the power line cyclostationary noise environment and compared against the performance in a stationary noise environment. As a result, it is confirmed that the power line and its cyclostationary noise features present an advantage against transmission in a channel with stationary noise.

In remote control, efficient compression or representation of control signals is essential to send them through rate-limited channels. For this purpose, we propose an approach of sparse control signal representation using the compressive sampling technique. The problem of obtaining sparse representation is formulated by cardinality-constrained ² optimization of the control performance, which is reducible to ¹-² optimization. The low rate random sampling employed in the proposed method based on the compressive sampling, in addition to the fact that the ¹-² optimization can be effectively solved by a fast iteration method, enables us to generate the sparse control signal with reduced computational complexity, which is preferable in remote control systems where computation delays seriously degrade the performance. We give a theoretical result for control performance analysis based on the notion of restricted isometry property (RIP). An example is shown to illustrate the effectiveness of the proposed approach via numerical experiments.

In a wireless multi-hop network between a source node (S) and a destination node (D), multipath routing in which S redundantly sends the same packets to D through multiple routes at the same time is effective for enhancing the reliability of the wireless data transmission by means of route diversity. However, when applying the multipath routing to a factory where huge robots are moving around, if closer multiple routes are selected, the probability that they are blocked by the robots at the same time becomes higher, so the reliability in terms of packet loss rate cannot be enhanced. In this paper, we propose a multipath routing method which can select physically distant multiple routes without any knowledge on the locations of nodes. We introduce a single metric composed of “the distance between routes” and “the route quality” by means of scalarization in multi-objective maximization problem and apply a genetic algorithm (GA) for searching for adequate routes which maximize the metric. Computer simulation results show that the proposed method can adaptively control the topologies of selected routes between S and D, and effectively reduce the packet loss rates.

This paper proposes a direction-of-arrival (DOA) estimation method of multiple speech sources from a stereophonic mixture in an underdetermined case where the number of sources exceeds the number of sensors. The method relies on the sparseness of speech signals in time-frequency (T-F) domain representation which means multiple independent speakers have a small overlap. At first, a selection of T-F cells bearing reliable spatial information is proposed by an introduced reliability index which is defined by the estimated interaural phase difference at each T-F cell. Then, a statistical error propagation model between the phase difference at T-F cell and its consequent DOA is introduced. By employing this model and the sparseness in T-F domain the DOA estimation problem is altered to obtaining local peaks of probability density function of DOA. Finally the kernel density estimator approach based on the proposed statistical model is applied. The performance of the proposed method is assessed by conducted experiments. Our method outperforms others both in accuracy for real observed data and in robustness for simulation with additional diffused noise.

This paper describes a method for estimating Direction Of Arrival (DOA) of multiple sound sources in full azimuth with three microphones. Estimating DOA with paired microphone arrays creates imaginary sound sources because of time delay of arrival (TDOA) being identical between real and imaginary sources. Imaginary sound sources can create chronic problems in multiple Sound Source Localization (SSL), because they can be localized as real sound sources. Our proposed approach is based on the observation that each microphone array creates imaginary sound sources, but the DOA of imaginary sources may be different depending on the orientation of the paired microphone array. With the fact that a real source would always be localized in the same direction regardless of the array orientation, we can suppress the imaginary sound sources by minimum filtering based on Steered Response Power – Phase Transform (SRP-PHAT) method. A set of experiments conducted in a real noisy environment showed that the proposed method was accurate in localizing multiple sound sources.

The frequency regions and spectral features that can be used to measure the perceived similarity and continuity of voice quality are reported here. A perceptual evaluation test was conducted to assess the naturalness of spoken sentences in which either a vowel or a long vowel of the original speaker was replaced by that of another. Correlation analysis between the evaluation score and the spectral feature distance was conducted to select the spectral features that were expected to be effective in measuring the voice quality and to identify the appropriate speech segment of another speaker. The mel-frequency cepstrum coefficient (MFCC) and the spectral center of gravity (COG) in the low-, middle-, and high-frequency regions were selected. A perceptual paired comparison test was carried out to confirm the effectiveness of the spectral features. The results showed that the MFCC was effective for spectra across a wide range of frequency regions, the COG was effective in the low- and high-frequency regions, and the effective spectral features differed among the original speakers.

In this paper, we propose a novel path tracking control algorithm for an underactuated autonomous underwater vehicle (AUV). The underactuated AUV is controlled by the thrust force and the yaw torque: no sway thruster is used. To deal with this underactuated AUV problem in the path tracking, we introduce an approach angle which makes the AUV converge to the reference path. To design the path tracking controller, we obtain the vehicle's error dynamics in the body-fixed frame, and then design the path tracking controller based on the dynamic surface control (DSC) method. The proposed controller only needs the information of the position and the heading angle of the reference path. Some simulation results demonstrate the effectiveness of the proposed controller.

The Viterbi algorithm is widely used for decoding of the convolutional codes. The trace-back method is preferable to the register exchange method because of lower power consumption especially for convolutional codes with many states. A drawback of the conventional trace-back is that it generally requires long latency to obtain the decoded data. In this paper, a method of the trace-back with source states instead of decision bits is proposed which reduces the number of memory accesses. The dedicated memory is also presented which supports the proposed trace-back method. The reduced memory accesses result in smaller power consumption and a shorer decode latency than the conventional method.

Zero-knowledge arguments allows one party to prove that a statement is true, without leaking any other information than the truth of the statement. In many applications such as verifiable shuffle (as a practical application) and circuit satisfiability (as a theoretical application), zero-knowledge arguments for mathematical statements related to linear algebra are essentially used. Groth proposed (at CRYPTO 2009) an elegant methodology for zero-knowledge arguments for linear algebraic relations over finite fields. He obtained zero-knowledge arguments of the sub-linear size for linear algebra using reductions from linear algebraic relations to equations of the form z=x*'y, where x, y ∈ Fⁿ_p are committed vectors, z ∈ F_p is a committed element, and *': Fⁿ_pFⁿ_pF_p is a bilinear map. These reductions impose additional rounds on zero-knowledge arguments of the sub-linear size. The round complexity of interactive zero-knowledge arguments is an important measure along with communication and computational complexities. We focus on minimizing the round complexity of sub-linear zero-knowledge arguments for linear algebra. To reduce round complexity, we propose a general transformation from a t-round zero-knowledge argument, satisfying mild conditions, to a (t-2)-round zero-knowledge argument; this transformation is of independent interest.

In the analysis of maximum-likelihood decoding performance of low-density parity-check (LDPC) codes, the weight distribution is an important factor. We presented a probabilistic method for computing the weight distribution of LDPC codes, and showed results of computing the weight distribution of several LDPC codes. In this paper, we improve our previously presented method and propose a probabilistic computation method with reliability for the weight distribution of LDPC codes. Using the proposed method, we can determine the weight distribution with small failure probability.

A recursive and efficient method for generating binary vectors in non-increasing order of their likelihood for a set of all binary vectors is proposed. Numerical results on experiments show the effectiveness of this method. Efficient decoding algorithms with simulation results are also proposed as applications of the method.

No nontrivial optimal sets of frequency-hopping sequences (FHSs) of period 2(2ⁿ-1) for a positive integer n ≥ 2 have been found so far, when their frequency set sizes are less than their periods. In this paper, systematic doubling methods to construct new FHS sets are presented under the constraint that the set of frequencies has size less than or equal to 2ⁿ. First, optimal FHS sets with respect to the Peng-Fan bound are constructed when frequency set size is either 2ⁿ-1 or 2ⁿ. And then, near-optimal FHS sets with frequency set size 2ⁿ-1 are designed by applying the Chinese Remainder Theorem to Sidel'nikov sequences, whose FHSs are optimal with respect to the Lempel-Greenberger bound. Finally, a general construction is given for near-optimal FHS sets whose frequency set size is less than 2ⁿ-1. Our constructions give new parameters not covered in the literature, which are summarized in Table1.

Non-negative matrix factorization (NMF) is widely used for monaural musical sound source separation because of its efficiency and good performance. However, an additional clustering process is required because the musical sound mixture is separated into more signals than the number of musical tracks during NMF separation. In the conventional method, manual clustering or training-based clustering is performed with an additional learning process. Recently, a clustering algorithm based on the mel-frequency cepstrum coefficient (MFCC) was proposed for unsupervised clustering. However, MFCC clustering supplies limited information for clustering. In this paper, we propose various timbre features for unsupervised clustering and a clustering algorithm with these features. Simulation experiments are carried out using various musical sound mixtures. The results indicate that the proposed method improves clustering performance, as compared to conventional MFCC-based clustering.

Reversible color component transforms derived by the LU factorization are briefly described. It is possible to obtain an reversible implementation to a given component transform, even if the original transform is irreversible. Some examples are presented and their performances are compared in image compression.

Keith Salvin presented a key exchange protocol using matrices in the general linear group, GL(r,Z_n), where n is the product of two distinct large primes. The system is fully specified in the US patent number 7346162 issued in 2008. In the patent claims, it is argued that the best way to break this system is to factor n. Furthermore, for efficiency reasons, it is suggested to use r=2. In this letter, we show that this cryptosystem can be easily broken by solving a set of consistent homogeneous r² linear equations in 2r unknowns over Z_n.

A new class of almost quadriphase sequences with four zero elements of period 4N, where N ≡ 1(mod 4) being a prime, is constructed. The maximum nontrivial autocorrelations of the constructed almost quadriphase sequences are shown to be 4.

In this letter, we present the evaluation of an option-based learning algorithm, developed to perform a conflict-free allocation of calls among cars in a multi-car elevator system. We evaluate its performance in terms of the service time, its flexibility in the task-allocation, and the load balancing.