Mixing vector construction for single channel semi-blind source separation using empirical mode decomposition

The Empirical Mode Decomposition (EMD) method is a commonly used method for solving the problem of single channel blind source separation (SCBSS) in signal processing. However, the mixing vector of SCBSS, which is the base of the EMD method, has not yet been effectively constructed. The mixing vector reflects the weights of original signal sources that form the single channel blind signal source. In this paper, we propose a novel method to construct a mixing vector for a single channel blind signal source to approximate the actual mixing vector in terms of keeping the same ratios between signal weights. The constructed mixing vector can be used to improve signal separations. Our method incorporates the adaptive filter, least square method, EMD method and signal source samples to construct the mixing vector. Experimental tests using audio signal evaluations were conducted and the results indicated that our method can improve the similar values of sources energy ratio from 0.2644 to 0.8366. This kind of recognition is very important in weak signal detection.

Prosthetic motor imaginary task classification using single channel of electroencephalography

Brain Computer Interface (BCI) is playing a very important role in human machine communications. Recent communication systems depend on the brain signals for communication. In these systems, users clearly manipulate their brain activity rather than using motor movements in order to generate signals that could be used to give commands and control any communication devices, robots or computers. In this paper, the aim was to estimate the performance of a brain computer interface (BCI) system by detecting the prosthetic motor imaginary tasks by using only a single channel of electroencephalography (EEG). The participant is asked to imagine moving his arm up or down and our system detects the movement based on the participant brain signal. Some features are extracted from the brain signal using Mel-Frequency Cepstrum Coefficient and based on these feature a Hidden Markov model is used to help in knowing if the participant imagined moving up or down. The major advantage in our method is that only one channel is needed to take the decision. Moreover, the method is online which means that it can give the decision as soon as the signal is given to the system. Hundred signals were used for testing, on average 89 % of the up down prosthetic motor imaginary tasks were detected correctly. This method can be used in many different applications such as: moving artificial prosthetic limbs and wheelchairs due to it's high speed and accuracy.

Motion artefact separation in single channel doppler radar respiration measurement

Direct conversion Doppler radar has the capability to remotely monitor human respiratory activity in a non-contact form. However, the motion or movement from the subject will degrade the acquired respiration signal. As the respiration pattern is one of the essential parameters in respiratory medicine intrinsically containing more information about the respiratory function, it is particularly important to suppress or to separate these motion artefacts in order to reconstruct the corresponding patterns. Experiment results show that EMD-ICA algorithm is capable of separating the mixed respiration signal by recovering the useful information of the breathing pattern as well as the motion signatures using only a single channel measurement when using the source separation algorithm. This reduces the complexity and the cost of the sensing system while removing the undesirable artefacts. A high correlation was also observed from the recovered respiration pattern in comparison to the standard respiration strap for both experiments setup (a seated and a supine position).

Detection of cross-channel anomalies from multiple data channels

We identify and formulate a novel problem: crosschannel anomaly detection from multiple data channels. Cross channel anomalies are common amongst the individual channel anomalies, and are often portent of significant events. Using spectral approaches, we propose a two-stage detection method: anomaly detection at a single-channel level, followed by the detection of cross-channel anomalies from the amalgamation of single channel anomalies. Our mathematical analysis shows that our method is likely to reduce the false alarm rate. We demonstrate our method in two applications: document understanding with multiple text corpora, and detection of repeated anomalies in video surveillance. The experimental results consistently demonstrate the superior performance of our method compared with related state-of-art methods, including the one-class SVM and principal component pursuit. In addition, our framework can be deployed in a decentralized manner, lending itself for large scale data stream analysis.

A shape error metric for sheet metal forming and its application to springback

There are many variations within sheet metal forming, some of which are manifest in the final geometry of the formed component. It is important that this geometric variation be quantified and measured for use in a process or quality control system. The contribution of this paper is to propose a novel way of measuring the geometric difference between the desired shape and an actual formed "U" channel. The metric is based upon measuring errors in terms of the significant manufacturing variations. The metric accords with the manually measured errors of the channel set. The shape error metric is then extended to develop a simple empirical, whole-component, springback error measure. The springback error measure combines into one value all the angle springback and side wall curl geometric errors for a single channel. Two trends were observed: combined springback decreases when the blank holder force is increased; and the combined springback marginally decreases when the die radii is increased.

Marketers' perceptions of the implementation difficulties of multichannel marketing

This paper identifies implementation difficulties associated with multichannel marketing as perceived by senior marketers. While, multichannel marketing is being increasingly used because of its revenue enhancing and cost reduction opportunities, it appears more difficult to implement than 'traditional' single channel marketing. Traditional strategy implementation frameworks as typified by Miles and Snow and Porter, do not appear to address the implementation complexities of multichannel strategies especially when considering the dynamism of contemporary external environments. Using the methodology of thematic analysis, three implementation difficulty themes were identified: (1) understanding multichannel customer behaviour; (2) delivering sales, service and pre-purchase information; and (3) dealing with organisational politics and conflict caused by emerging channels. We propose that dynamic strategic frameworks can better address complexity and uncertainty, and overcome implementation difficulties. The paper concludes with general and specific research propositions to test the effectiveness of dynamic strategic frameworks in terms of the three themes.

Prosthetic motor imaginary task classification based on EEG quality assessment features

Brain Computer Interface (BCI) plays an important role in the communication between human and machines. This communication is based on the human brain signals. In these systems, users use their brain instead of the limbs or body movements to do tasks. The brain signals are analyzed and translated into commands to control any communication devices, robots or computers. In this paper, the aim was to enhance the performance of a brain computer interface (BCI) systems through better prosthetic motor imaginary tasks classification. The challenging part is to use only a single channel of electroencephalography (EEG). Arm movement imagination is the task of the user, where (s)he was asked to imagine moving his arm up or down. Our system detected the imagination based on the input brain signal. Some EEG quality features were extracted from the brain signal, and the Decision Tree was used to classify the participant's imagination based on the extracted features. Our system is online which means that it can give the decision as soon as the signal is given to the system (takes only 20 ms). Also, only one EEG channel is used for classification which reduces the complexity of the system which leads to fast performance. Hundred signals were used for testing, on average 97.4% of the up-down prosthetic motor imaginary tasks were detected correctly. This method can be used in many different applications such as: moving artificial limbs and wheelchairs due to it's high speed and accuracy.

CM-based blind equalization of time-varying SIMO-FIR channel with single pulsation estimation

It is known that the constant modulus (CM) property of the source signal can be exploited to blindly equalize time-invariant single-inputmultiple-output (SIMO) and finite-impulse-response (FIR) channels. However, the time-invariance assumption about the channel cannot be satisfied in several practical applications, e.g., mobile communication. In this paper, we show that, under some mild conditions, the CM criterion can be extended to the blind equalization of a time-varying channel that is described by the complex exponential basis expansion model (CE-BEM). Although several existing blind equalization methods that are based on the CE-BEM have to employ higher order statistics to estimate all nonzero channel pulsations, the CM-based method only needs to estimate one pulsation using second-order statistics, which yields better estimation results. It also relaxes the restriction on the source signal and is applicable to some classes of signals with which the existing methods cannot deal.

Deformation and annealing of (011)[011] oriented A1 single crystals

High purity Al single crystals of the (011)[011] orientation have been deformed in plane strain compression in a channel die. Deformation was carried out at a strain rate of 0.01 s−1 to true strains of 0.5 and 1.0, and at temperatures of 25, 200 and 300 °C. The as-deformed microstructure has been characterized using electron backscattered diffraction (EBSD) and X-ray diffraction (XRD). No recrystallization was detected after deformation, and the deformation texture analysis showed that the stability of the orientation decreased with increasing temperature, contrary to reports for other orientations.

Annealing was carried out for various times at 300 °C. Nucleation of recrystallization exhibited periodicity, with distinct bands of recrystallized grains forming parallel to the transverse direction. This recrystallized microstructure has been examined using EBSD. A model is proposed to account for the origin of the periodicity of nucleation and the retention of rods or cylinders of unrecrystallized material after significant annealing times.

A qualitative study of multi-channel marketing performance measurement issues

The aim of this study was to provide quantitative research propositions for future researchers studying multi-channel marketing performance. The literature suggests that multi-channel marketing is becoming more prevalent and offers many opportunities to organisations. Multi-channel marketing is, however, more complex to implement and measure than 'traditional' single or dual-channel marketing. Thirty-one senior marketing executives from a diverse range of industries were asked to provide a 'single key challenge' in the area of multi-channel marketing. The findings suggest that the main areas of multi-channel marketing measurement problems are: (a) understanding return on channel investment, (b) understanding customer channel preference and (c) isolating individual channel impact. The paper concludes by using both the qualitative findings and implementation theory to provide propositions for future research as well as tentative management Guidelines.

Is the ultraviolet waveband a special communication channel in avian mate choice?

There is growing evidence that ultraviolet (UV) wavelengths play an important role in avian mate choice. One of the first experiments to support this idea showed that female zebra finches (Taeniopygia guttata) prefer UV-reflecting males to males whose ultraviolet reflection has been removed. The effect was very strong despite little or no UV reflection from several plumage areas. However, it is not clear how the importance of the UV waveband compares to other regions of the bird-visible spectrum. We tested whether the response of female zebra finches to the removal of male UV reflection is greater than to the removal of other wavebands. We presented females with a choice of males whose appearance was manipulated using coloured filters. The filters removed single blocks of the avian visible spectrum corresponding closely to the spectral sensitivities of each of the zebra finch's single cone classes. This resulted in males that effectively had no UV (UV-), no short-wave (SW-), no medium-wave (MW-) or no long-wave (LW-) plumage reflection. Females preferred UV- and SW- males. LW- and MW- males were least preferred, suggesting that female zebra finches show the greatest response to the removal of longer wavelengths. Quantal catches of the single cone types viewing body areas of the male zebra finch are presented for each treatment. Our study suggests it is important to consider the role of the UV waveband in avian mate choice in conjunction with the rest of the avian visible spectrum.

Effect of orientation stability on recrystallization textures of deformed aluminium single crystals

High purity Al single crystals of the Cube (0 0 1)[1 0 0] and rotated Cube (0 1 1)[0 1 ¯ 1] orientations have been deformed in plane strain compression in a channel die. Deformation was carried out at temperatures between 25 and 600 8C up to strains of 1.2. The as-deformed microstructure has been characterised using electron microscopy and electron backscattered diffraction (EBSD).
Annealing was carried out for various times and temperatures. The recrystallized microstructure has been studied using electron microscopy, and the orientation of recrystallized grains determined using EBSD. After cold deformation and annealing both orientations exhibited a random recrystallization texture component. After hot deformation both orientations retained a similar annealing texture to their starting deformation texture. The annealing texture of deformed single crystals was found to be more sensitive to the temperature of deformation than the stability of the orientation.

A new adaptive blind channel identification algorithm

This paper addresses the blind identification of single-input multiple-output (SIMO) finite-impulse-response (FIR) systems. We first propose a new adaptive algorithm for the blind identification of SIMO FIR systems. Then, its convergence property is analyzed systematically. It is shown that under some mild conditions, the proposed algorithm is guaranteed to converge in the mean to the true channel impulse responses in both noisy and noiseless cases. Simulations are carried out to demonstrate the theoretical results.

Low complexity MMSE based channel estimation technique for LTE OFDMA systems

Long term evolution (LTE) is designed for high speed data rate, higher spectral efficiency, and lower latency as well as high-capacity voice support. LTE uses single carrierfrequency division multiple access (SC-FDMA) scheme for the uplink transmission and orthogonal frequency division multiple access (OFDMA) in downlink. The one of the most important challenges for a terminal implementation are channel estimation (CE) and equalization. In this paper, a minimum mean square error (MMSE) based channel estimator is proposed for an OFDMA systems that can avoid the ill-conditioned least square (LS) problem with lower computational complexity. This channel estimation technique uses knowledge of channel properties to estimate the unknown channel transfer function at non-pilot subcarriers.

Channel estimation scheme for 3.9G wireless communication systems using RLS algorithm

Main challenges for a terminal implementation are efficient realization of the receiver, especially for channel estimation (CE) and equalization. In this paper, training based recursive least square (RLS) channel estimator technique is presented for a long term evolution (LTE) single carrier-frequency division multiple access (SC-FDMA) wireless communication system. This CE scheme uses adaptive RLS estimator which is able to update parameters of the estimator continuously, so that knowledge of channel and noise statistics are not required. Simulation results show that the RLS CE scheme with 500 Hz Doppler frequency has 3 dB better performances compared with 1.5 kHz Doppler frequency.