We present an improvement to the existing steganography-based bandwidth extension scheme. Enhanced WB (wideband) speech quality is achieved by embedding multiple highband spectral gains into a G.711 bitstream. The number of spectral gains is selected by optimizing the quantity of the embedding data with respect to the quality of the extended WB speech. Compared to the existing method, the proposed scheme improves the WB PESQ (Perceptual Evaluation of Speech Quality) score by 0.334 with negligible degradation of the embedded narrowband speech.

In this paper, we present a distributed and interactive admission and power control protocol for spectrum underlay environments. The protocol enables distributed primary users (PUs) to estimate and adjust the level of tolerable interference as their transmitting powers evolve to a given signal-to-interference-plus-noise ratio (SINR) target. The protocol also guides the powers of distributed secondary users (SUs) to achieve their own targets while restricting the transmitting powers from SUs so as not to interfere with the PUs. This restriction of interference from SUs to PUs is an essential part of cognitive radio networks (CRNs) and is facilitated by sending a warning tone from PUs to SUs in the proposed protocol. The SUs that have frequently received the warning tones turn off their transmitters and so autonomously drop from the system. This paper proves that, under the proposed interactive protocol, every PU finally achieves its target if it is originally feasible without SUs and the transmit powers of remaining SUs converge to a fixed point. The proposed method protects PUs perfectly in the sense that all the PUs reach their targets after power control. Numerical investigation shows how safely PUs are protected and how well SUs are admitted as a function of protocol parameters, the frequency of warning tones, the number of SUs to be admitted and the number of active PUs.

In this paper, a novel visual signal reliability (VSR) measure is proposed to consider video degradation at the signal level in audio-visual speaker identification (AVSI). The VSR estimation is formulated using a~ Gaussian fuzzy membership function (GFMF) to measure lighting variations. The variance parameters of GFMF are optimized in order to maximize the performance of the overall AVSI. The experimental results show that the proposed method outperforms the score-based reliability measuring technique.

This study develops a fuzzy logic control mechanism in eigenspace-based MLLR speaker adaptation. Specifically, this mechanism can determine hidden Markov model parameters to enhance overall recognition performance despite ordinary or adverse conditions in both training and operating stages. The proposed mechanism regulates the influence of eigenspace-based MLLR adaptation given insufficient training data from a new speaker. This mechanism accounts for the amount of adaptation data available in transformation matrix parameter smoothing, and thus ensures the robustness of eigenspace-based MLLR adaptation against data scarcity. The proposed adaptive learning mechanism is computationally inexpensive. Experimental results show that eigenspace-based MLLR adaptation with fuzzy control outperforms conventional eigenspace-based MLLR, and especially when the adaptation data acquired from a new speaker is insufficient.

In order to study the influences of contact opening speeds on arc extinction gap length characteristics, Ag contacts were operated to break DC inductive load currents from 0.1 A to 2.0 A at 14 V with contact opening speeds of 0.5 mm/s, 1 mm/s, 2 mm/s, 5 mm/s and 10 mm/s in a switching mechanism employing a stepping motor, and arc voltage waveforms were observed at each opening of the contacts. From the results, the average arc durations were determined at each current level under the respective contact opening speeds, and the average arc extinction gap lengths were calculated by multiplying the average arc duration value and the contact opening speed value. It was found that average arc durations showed no significant differences with increasing contact opening speeds. Thus, arc extinction gaps became larger at faster opening speeds in the inductive load conditions of this study.

A non-audible murmur (NAM), a very weak whisper sound produced without vocal fold vibration, has been researched in the development of a silent-speech communication tool for functional speech disorders as well as human-to-human/machine interfaces with inaudible voice input. The NAM can be detected using a specially designed microphone, called a NAM microphone, attached to the neck. However, the detected NAM signal has a low signal-to-noise ratio and severely suppressed high-frequency component. To improve NAM clarity, the mechanism of a NAM production must be clarified. In this work, an air flow through a glottis in the vocal tract was numerically simulated using computational fluid dynamics and vocal tract shape models that are obtained by a magnetic resonance imaging (MRI) scan for whispered voice production with various strengths, i.e. strong, weak, and very weak. For a very weak whispering during the MRI scan, subjects were trained, just before the scanning, to produce the very weak whispered voice, or the NAM. The numerical results show that a weak vorticity flow occurs in the supraglottal region even during a very weak whisper production; such vorticity flow provide aeroacoustic sources for a very weak whispering, i.e. NAM, as in an ordinary whispering.

In this paper, we propose a new method to estimate and effectively reduce the effect of thermal asperity (TA) in the perpendicular magnetic recording (PMR) channels with the state trellis. The TA is estimated from the state trellis, then its average is used to modify the equalized signal entering the Viterbi detector. For the partial response (PR) targets with DC component, the proposed method with a maximum-likelihood detector can improve the bit error rate performance by more than an order of magnitude when TA occurs and degrades when the giant magneto-resistive (GMR) nonlinearity and base line wander (BLW) effects are present. Unlike the previous studies, this method allows the use of PR targets with DC component under the presence of TA.

A hybrid overlay/underlay spectrum sharing method for cognitive radio networks based on user classification and convex optimization is proposed. Interference radii are configured for the primary receiver and each cognitive receiver. Cognitive users are divided into four groups and allocated different spectrum sharing patterns according to their distance from the primary transmitter and receiver. An optimal power allocation scheme that achieves the maximum sum rate of cognitive radio system on the premise of satisfying the interference constraint of primary receiver is acquired through the convex optimization method. Performance analysis and simulation results show that, compared with existing methods, our method leads to improved performance of achievable sum rate of cognitive users while guarantees the transmission of primary users.

A spectrum sensing scheme for cognitive radio that includes coarse and fine sensing stages based on cyclostationarity is proposed in this paper. The cyclostationary feature detection (CFD) based on a single cyclic frequency (SCF) is used in the coarse sensing stage and that based on multiple cyclic frequencies (MCF) is employed in the fine sensing stage. Whether the fine sensing stage is performed or not is decided by comparing the statistic constructed in the coarse sensing stage with two thresholds. Theoretical analyses and simulation results show that the proposed sensing scheme has superior sensing performance and needs shorter sensing time.

Cognitive radio (CR) is a key solution for the problem of inefficient usage of spectral resources. Spectrum sensing in each CR aims at detecting whether a preassigned spectrum band is occupied by a primary user or not. Conventional techniques do not allow the CR to communicate with its own base station during the spectrum sensing process. So, only a part of the frame can be used for cognitive data transmission. In this paper, we introduce a new spectrum sensing framework that combines a blind source separation technique with conventional spectrum sensing techniques. In this way, the cognitive transmitter can continue to transmit during spectrum sensing, if it was in operation in the previous frame. Moreover, the accuracy is improved since the decision made by the spectrum unit in each frame depends on the decision made in the previous frame. We use Markov chain tools to model the behavior of our spectrum sensing proposal and to derive the parameters that characterize its performance. Numerical results are provided to confirm the superiority of the proposed technique compared to conventional spectrum sensing techniques.

Break arcs are rotated with the radial magnetic field formed by a magnet embedded in the fixed contact. They are generated in a DC42 V resistive circuit. The circuit current when the contacts are closed varies from 5 A to 21 A. The strength of a radial magnetic field for rotating break arcs changes. Arc duration is investigated. Then rotational frequency, arc length and Lorentz force when the periodic rotation of break arcs starts are analyzed to investigate the conditions required to rotate break arcs. The following results are obtained. The arc length L when the rotational motion of the break arc starts is almost constant at a constant magnetic flux density with an increase in circuit current. The arc length L decreases with an increase in the magnetic flux density of the radial magnetic field. The rotational motion of break arcs starts when the arc length L reaches a certain value determined by magnetic flux density. Rotational frequency and Lorentz force increase linearly with an increase in circuit current.

Silver electrical contacts are separated to generate break arcs in a DC48 V/6-24 A resistive circuit. The transverse magnetic field formed by a permanent magnet is applied to the break arcs. A series of experiments are carried out for two different experimental conditions. One condition is a constant contact separating speed while the magnetic flux density is changed to investigate the shortening effect of the arc duration. Another condition is a constant magnetic flux density while the contact separating speed is changed to investigate the changes in the arc duration and the contact gap when the break arc is extinguished. As a result, with constant separating speed, it is confirmed that the duration of break arcs is shortened by the transverse magnetic field and the break arcs are extinguished when the arc length reaches a certain value L. Under the condition of constant transverse magnetic field, (i) the arc duration is shortened by increasing the separation speed; (ii) the contact gap when the break arc is extinguished is almost constant when the separating speed v is sufficiently faster than 5 mm/s.

Numerous noise suppression methods for speech signals have been developed up to now. In this paper, a new method to suppress noise in speech signals is proposed, which requires a single microphone only and doesn't need any priori-information on both noise spectrum and pitch. It works in the presence of noise with high amplitude and unknown direction of arrival. More specifically, an adaptive noise suppression algorithm applicable to real-life speech recognition is proposed without assuming the Gaussian white noise, which performs effectively even though the noise statistics and the fluctuation form of speech signal are unknown. The effectiveness of the proposed method is confirmed by applying it to real speech signals contaminated by noises.

In this letter, we focus on the spectrum sharing cognitive radio system, wherein a single-input multi-output cognitive fading channel is considered. Subject to the joint average interference constraint and peak interference constraint at the primary receiver, the outage capacity of the cognitive channel involving joint beamforming and power control is analyzed. We derive the optimal beamforming and power control strategy and deduce the closed-form expression for the outage capacity under Rayleigh fading model, the functional regions of two kinds of interference constraints are discussed as well. Furthermore, considering zero-outage transmission, we investigate the delay-limited capacity and introduce a new concept called the zero-outage average interference wall. Extensive simulations corroborate our theoretical results.

In this paper, we present an approach of detecting speech presence for which the decision rule is based on a combination of multiple features using a sigmoid function. A minimum classification error (MCE) training is used to update the weights adjustment for the combination. The features, consisting of three parameters: the ratio of ZCR, the spectral energy, and spectral entropy, are combined linearly with weights derived from the sub-band domain. First, the Bark-scale wavelet decomposition (BSWD) is used to split the input speech into 24 critical sub-bands. Next, the feature parameters are derived from the selected frequency sub-band to form robust voice feature parameters. In order to discard the seriously corrupted frequency sub-band, a strategy of adaptive frequency sub-band extraction (AFSE) dependant on the sub-band SNR is then applied to only the frequency sub-band used. Finally, these three feature parameters, which only consider the useful sub-band, are combined through a sigmoid type function incorporating optimal weights based on MSE training to detect either a speech present frame or a speech absent frame. Experimental results show that the performance of the proposed algorithm is superior to the standard methods such as G.729B and AMR2.

We propose an active noise control (ANC) system for reducing periodic noise generated in a high magnetic field such as noise generated from magnetic resonance imaging (MRI) devices (MR noise). The proposed ANC system utilizes optical microphones and piezoelectric loudspeakers, because specific acoustic equipment is required to overcome the high-field problem, and consists of a head-mounted structure to control noise near the user's ears and to compensate for the low output of the piezoelectric loudspeaker. Moreover, internal model control (IMC)-based feedback ANC is employed because the MR noise includes some periodic components and is predictable. Our experimental results demonstrate that the proposed ANC system (head-mounted structure) can significantly reduce MR noise by approximately 30 dB in a high field in an actual MRI room even if the imaging mode changes frequently.

In this paper, a preemptive priority queueing model is developed to derive the system dwelling time of secondary calls in a cognitive radio system in which a primary call's reoccupation of the channel is modeled as a preemptive event that forces a secondary call to attempt a spectrum handover. The suspension of secondary call service which may happen when the immediate spectrum handover fails, is included in our computation of the system dwelling time. The results are helpful in evaluating cognitive radio systems in terms of service delay and in determining system design parameters such as required buffer size and system capacity.

The problem of estimating the nominal angles and angular spreads of multiple coherently distributed (CD) sources in a symmetric uniform linear array (ULA) is considered. Based on structure of the subarrays consisting of two opposite sensors relative to the center of a ULA and the rank reduction (RARE) concept, the proposed algorithm is able to estimate the nominal angles without any angular signal density model assumptions of the sources. Using the estimated nominal angles, the angular spread of each source is then obtained using a one-dimensional (1-D) distributed source parameter estimator (DSPE).

In this paper, we propose a text corpus design method for a Korean stereo super-wideband speech database. Since a small-sized text corpus for speech coding is generally required for speech coding, the corpus should be designed to comply with the pronunciation behavior of natural conversation in order to ensure efficient speech quality tests. To this end, the proposed design method utilizes a similarity measure between the phoneme distribution occurring from natural conversation and that from the designed text corpus. In order to achieve this goal, we first collect and refine text data from textbooks and websites. Next, a corpus is designed from the refined text data based on the similarity measure to compare phoneme distributions. We then construct a Korean stereo super-wideband speech (K-SW) database using the designed text corpus, where the recording environment is set to meet the conditions defined by ITU-T. Finally, the subjective quality of the K-SW database is evaluated using an ITU-T super-wideband codec in order to demonstrate that the K-SW database is useful for developing and evaluating super-wideband codecs.

Although the Marching Cube (MC) algorithm is very popular for displaying images of voxel-based objects, its slow surface extraction process is usually considered to be one of its major disadvantages. It was pointed out that for the original MC algorithm, we can limit vertex calculations to once per vertex to speed up the surface extraction process, however, it did not mention how this process could be done efficiently. Neither was the reuse of these MC vertices looked into seriously in the literature. In this paper, we propose a “Group Marching Cube” (GMC) algorithm, to reduce the time needed for the vertex identification process, which is part of the surface extraction process. Since most of the triangle-vertices of an iso-surface are shared by many MC triangles, the vertex identification process can avoid the duplication of the vertices in the vertex array of the resultant triangle data. The MC algorithm is usually done through a hash table mechanism proposed in the literature and used by many software systems. Our proposed GMC algorithm considers a group of voxels simultaneously for the application of the MC algorithm to explore interesting features of the original MC algorithm that have not been discussed in the literature. Based on our experiments, for an object with more than 1 million vertices, the GMC algorithm is 3 to more than 10 times faster than the algorithm using a hash table. Another significant advantage of GMC is its compatibility with other algorithms that accelerate the MC algorithm. Together, the overall performance of the original MC algorithm is promoted even further.