Heart sound cancellation based on multiscale products and linear prediction

This paper presents a novel method for Heart Sound (HS) cancellation from Lung Sound (LS) records. The method uses the multiscale product of the wavelet coefficients of the original signal to detect HS-included segments. Once the HS segments are identified, the method removes them from the wavelet coefficients at every level and estimates the created gaps by using a set of linear prediction filters. It is shown that if the segment to be predicted is stationary, a final record with no audible artifacts such as clicks can be reconstructed using this approach. The results were promising for HS removal from LS records and showed no hampering of the main components of the LS. The results were confirmed both qualitatively by listening to the reconstructed signal and quantitatively by spectral analysis.     

Spin Crossover of Yb2+ in CsCaX3 and CsSrX3 (X = Cl,Br, I) – A Guideline to Novel Halide‐Based Scintillators

In this paper, the temperature dependence of the photoluminescence of Yb²⁺ doped into the halidoperovskites CsMX₃ (M = Ca, Sr; X = Cl, Br, I) is presented. Yb²⁺ shows spin‐forbidden high‐spin (HS) and spin‐allowed low‐spin (LS) emission bands in all compounds. Upon excitation of the higher energetic LS transition, very different behaviors of the interplay of the two emissive transitions are observed. In the chlorides, the HS‐based emission becomes already dominant at higher temperatures than 50 K; in the bromides, a temperature‐dependent population of the HS state is observed at higher temperatures than 200 K, whereas in the iodides, the LS emission remains dominant even above 300 K. A vibrational relaxation model is attempted for the explanation of this behavior that reveals a very delicate dependence on the mode energies of the [YbX₆]^4? octahedra. FIR spectra of the pure Yb²⁺‐based compounds CsYbX₃ are also presented to experimentally verify the estimated average mode energies from the model. Finally, the relevance for novel Yb²⁺‐based scintillators is discussed.     

New block filtered-X LMS algorithms for active noise control systems

New block formulations for an active noise control (ANC) system using only convolution machines are presented. The proposed approaches are different from conventional block least-mean-square (LMS) algorithms that use both convolution and cross-correlation machines. The block implementation is also applied to the filtering of the reference signal by the secondary-path estimate. In addition to the use of the fast Fourier transform (FFT), the fast Hartley transform (FHT) is used to develop transform-domain ANC structures for reducing computational complexity. In the proposed approach, some FFT and FHT blocks are removed to obtain an additional reduction of the computational burden resulting in the reduced-structure of FFT-based block filtered-X LMS (FBFXLMS) and FHT-based block filtered-X LMS (HBFXLMS) algorithms. The computational complexities of these new ANC structures are evaluated.     

New unbiased adaptive IIR filter: it’s robust and variable step-size versions and application to active noise control

This paper proposes a robust variable step-size adaptive IIR filter realized by a new bias-free structure (BFS). Unlike equation error (EQE) method that uses a desired signal contaminated with observation noise, the BFS employs a filter driven by the output of the plant estimate and this achieves a bias-free estimate of the denominator of the system function. In addition, the adaptation is made robust to the observation noise by the Griffiths’ LMS adaptation, which uses the cross-correlation estimate between the input and the desired signal for its adaptation gradient computation. A robust variable step-size adaptation is also realized by the Griffiths’ gradient. The proposed structure is referred to as BFSGV and has good modeling capability with improved convergence rate and reduced misadjustment. For system identification, the proposed BFSGV algorithm gives a 3 dB improvement in the performance index over EQE method. The proposed BFSGV has been applied to active noise control (ANC). The BSFGV structure is used for secondary path (SP) estimation, and for the main path (MP), BFS structure with step-size varied according to Okello’s method (BSFV) is used. The new ANC system for narrowband noise field is found to be having 4 times faster convergence rate and an additional noise reduction of 15dB over that FIR for MP and the EQE for SP. Further, the use of the proposed ANC IIR algorithm achieves computational savings compared to that of FIR. For the broadband noise field, the proposed method that uses BSFV for MP and BSFGV for SP provides 18 times faster convergence rate and 2.5 dB reduction in ANC error compare to that of the ANC using FIR for MP and the EQE for SP estimation.     

基于最大混合相关熵准则的主动噪声控制算法

为了处理脉冲噪声，传统的滤波x最大相关熵准则（filtered-x maximum correntropy criterion，FxMCC）自适应算法具有良好的降噪性能在主动噪声控制(active noise control，ANC)系统中。然而，FxMCC算法具有单一的高斯核，其降噪性能和收敛速度易受到核宽度取值的影响。因此，在ANC系统中，本文采用最大混合相关熵准则（maximum mixture correntropy criterion，MMCC），以两个高斯核的混合作为代价函数来推导滤波x最大混合相关熵准则（filtered-x maximum mixture correntropy criterion，FxMMCC）算法。仿真结果表明，在标准对称α稳定（symmetric α-stable, SαS）分布的脉冲噪声的主动噪声控制中，本文提出的FxMMCC算法比其它ANC算法具有更好的降噪性能。      

Adaptive Volterra filters for active control of nonlinear noiseprocesses

This paper presents a Volterra filtered-X least mean square (LMS) algorithm for feedforward active noise control. The research has demonstrated that linear active noise control (ANC) systems can be successfully applied to reduce the broadband noise and narrowband noise, specifically, such linear ANC systems are very efficient in reduction of low-frequency noise. However, in some situations, the noise that comes from a dynamic system may he a nonlinear and deterministic noise process rather than a stochastic, white, or tonal noise process, and the primary noise at the canceling point may exhibit nonlinear distortion. Furthermore, the secondary path estimate in the ANC system, which denotes the transfer function between the secondary source (secondary speaker) and the error microphone, may have nonminimum phase, and hence, the causality constraint is violated. If such situations exist, the linear ANC system will suffer performance degradation. An implementation of a Volterra filtered-X LMS (VFXLMS) algorithm based on a multichannel structure is described for feedforward active noise control. Numerical simulation results show that the developed algorithm achieves performance improvement over the standard filtered-X LMS algorithm for the following two situations: (1) the reference noise is a nonlinear noise process, and at the same time, the secondary path estimate is of nonminimum phase; (2) the primary path exhibits the nonlinear behavior. In addition, the developed VFXLMS algorithm can also be employed as an alternative in the case where the standard filtered-X LMS algorithm does not perform well     

Feedback active noise control based on transform-domain forward–backward LMS predictor

In this paper, a new feedback active noise control (FBANC) system based on the transform-domain forward–backward LMS (TFBLMS) predictor has been proposed. The new ANC system employs the TFBLMS predictor for its main-path (MP) predictor as well as for the noise canceller. To overcome the ill effect of the primary noise field, which acts as an observation noise for the secondary-path (SP) identification, the noise canceller is used. As the main-path predictor is based on the TFBLMS, its convergence rate improves due to its input orthogonalization. Further, its FBLMS nature reduces misadjustment. The use of TFBLMS predictor for noise canceller also gives a good prediction of primary noise at a faster rate, enabling improved SP identification. This improved SP identification indirectly aids the MP predictor to achieve an improved performance. A new filtered-x LMS structure has been proposed to realize the new MP predictor to accommodate the TFBLMS algorithm. The TFBLMS algorithm is applied directly to the noise canceller for SP identification. The proposed new ANC system has been found to have a significantly better noise reduction (by 14.6 dB) over the FBANC system based on tapped delay line time-domain FBLMS algorithm.     

Adaptive noise cancellation in a multimicrophone system for distortion product otoacoustic emission acquisition

This study focuses on adaptive noise cancellation (ANC) techniques for the acquisition of distortion product otoacoustic emissions (DPOAEs). Otoacoustic emissions (OAEs) are very low level sounds produced by the outer hair cells of normal cochleas, spontaneously or in response to sound stimulation as a byproduct of a frequency and threshold sensitivity increasing mechanism. Current OAE recording systems rely on test probe noise attenuation and synchronous ensemble averaging for increasing signal-to-noise ratios (SNRs). The efficiency of an ANC algorithm for noise suppression was investigated using three microphones: one placed in the test ear, one in the nontest ear for internal noise reference; one near the subject's head for external noise reference. The system proposed was tested with simulations, off-line averaging and real-time implementation of the ANC algorithm. Simulation results showed that the technique had a potential noise reduction capability of 24 dB for complex multifrequency noise signals. Off-line results were positive, with a mean SNR improvement of 4.9 dB. Real-time results indicated that the use of an ANC algorithm in combination with standard averaging methods can reduce noise levels by as much as 10 dB beyond that obtained with standard noise reduction methods and probe attenuation alone.     

Passive and Active Reduction Techniques for On-Chip High-Frequency Digital Power Supply Noise

Signal integrity has become a major problem in digital IC design. One cause is device scaling that results in a sharp reduction of supply voltage, creating stringent noise margin requirements to ensure functionality. This paper introduces both a novel on-chip decoupling capacitance methodology and active noise cancellation (ANC) structure. The decoupling methodology focuses on quantification and location. The ANC structure, with an area of 50 $mu {hbox {m}} times,55 mu{hbox {m}}$, uses decoupling capacitance to sense noise and inject a proportional current into $V _{rm SS}$ as a method of reduction. A chip has been designed and fabricated using TSMC's 90-nm technology. Measurements show that the decoupling methodology improved the average voltage headroom loss by 17% while the ANC structure improved the average voltage headroom loss by 18%.      

Active control of nonlinear noise processes in a linear duct

This paper investigates two scenarios in active noise control (ANC) that lead to performance degradation with conventional linear control techniques. The first scenario addresses the noise itself. The low-frequency noise, traveling as plane waves in a duct, is usually assumed to be broadband random or periodic tonal noise. Linear techniques applied to actively control this noise have been shown to be successful. However, in many practical applications, the noise often arises from dynamical systems, which cause the noise to be nonlinear and deterministic or stochastic, colored, and non-Gaussian. Linear techniques cannot fully exploit the coherence in the noise and, therefore, perform suboptimally. The other scenario is that the actuator in an ANC system has been shown to be nonminimum phase. One of the tasks of the controller, in ANC systems, is to model the inverse of the actuator. Obviously, a linear controller is not able to perform that task. To combat the problems, as mentioned above, a nonlinear controller has been implemented in the ANC system. It is shown in this paper that the nonlinear controller consists of two parts: a linear system identification part and a nonlinear prediction part. The standard filtered-x algorithms cannot be used with a nonlinear controller, and therefore, the control scheme was reconfigured. Computer simulations have been carried out and confirm the theoretical derivations for the combined nonlinear and linear controller     

基于WLSE-KF的传感器融合定位算法研究

多传感器融合在定位中的应用越来越广泛。在利用这些传感器进行定位的过程中,需要对其采集的数据进行融合。射频识别融合定位一般采用最小二乘法,然而,它可能使定位误差较大。文中提出了将最小二乘和卡尔曼滤波相结合的算法。该算法先利用加权最小二乘估计获得移动用户的初步位置,再利用扩展卡尔曼滤波进一步使定位精度得到提高。仿真结果表明该算法相比多种传统定位算法,误差减少,定位精度明显提高。     

A robust method for heart sounds localization using lung sounds entropy

Heart sounds are the main unavoidable interference in lung sound recording and analysis. Hence, several techniques have been developed to reduce or cancel heart sounds (HS) from lung sound records. The first step in most HS cancellation techniques is to detect the segments including HS. This paper proposes a novel method for HS localization using entropy of the lung sounds. We investigated both Shannon and Renyi entropies and the results of the method using Shannon entropy were superior. Another HS localization method based on multiresolution product of lung sounds wavelet coefficients adopted from was also implemented for comparison. The methods were tested on data from 6 healthy subjects recorded at low (7.5 ml/s/kg) and medium 115 ml/s/kg) flow rates. The error of entropy-based method using Shannon entropy was found to be 0.1 +/- 0.4% and 1.0 +/- 0.7% at low and medium flow rates, respectively, which is significantly lower than that of multiresolution product method and those of other methods reported in previous studies. The proposed method is fully automated and detects HS included segments in a completely unsupervised manner.     

An adaptive noise canceller with low signal distortion for speechcodecs

This paper proposes an adaptive noise canceller (ANC) with low signal distortion for speech codecs. The proposed ANC has two adaptive filters: a main filter (MF) and a subfilter (SF). The signal-to-noise ratio (SNR) of input signals is estimated using the SF. To reduce signal distortion in the output signal of the ANC, a step size for coefficient update in the MF is controlled according to the estimated SNR. Computer simulation results using speech and diesel engine noise recorded in a special-purpose vehicle show that the proposed ANC reduces signal distortion in the output signal by up to 15 dB compared with a conventional ANC. Results of subjective listening tests show that the mean opinion scores (MOSs) for the proposed ANC with and without a speech codec are one point higher than the scores for the conventional ANC     

New aspects to event-synchronous cancellation of ECG interference: an application of the method in diaphragmatic EMG signals

An "event-synchronous interference canceller" (ESC) for cancellation of electrocardiographic (ECG) interference in diaphragmatic electromyographic (EMGdi) signals is addressed in this paper. ESC pursues the concept of the "event synchronous adaptive interference canceller" (ESAIC), which was proposed in [1] as a specific application of the well known "adaptive noise canceller" (ANC) paradigm, but ESC uses a simple adaptive gain control (AGC) instead of the complex adaptive filter of the ANC. The proposed ESC method is evaluated using both computer simulations and real EMGdi data, and its efficiency in interference cancellation is compared to that of ESAIC. Of particular interest is the result that the ESC can replace the ESAIC providing better performance as well as a considerable reduction of computational costs.     

Atomic force microscopy proposes a 'kiss and pull' mechanism for enhancer function. off

The DNase I-hyper-sensitive sites (HS2-HS4) in the beta-globin gene enhancer region (locus control region; LCR) have been known as the target of Bach1/MafK heterodimers. We have demonstrated previously by utilizing atomic force microscopy (AFM) that Bach1/MafK mediates the formation of a looped-DNA structure in the LCR fragment. Here we perform further detailed analyses of the loop structure formed between each HSs by AFM, and propose a novel model for the enhancer/protein interaction: the Bach1/MafK heterodimer preferentially binds to HS2 with highest affinity and to HS3 with lower affinity. However, they assemble to each other to form a stable complex of four heterodimers and mediate a DNA-loop formation. Once the DNA loop is formed between HS2 and HS3, the Bach1/MafK complex at the HS3 side leaves the HS3 and starts to slide along the DNA strand towards HS2 with the other side of the complex fixed at the HS2 region. This 'kiss and pull' model will contribute to understand the function of regulatory proteins at enhancer regions in terms of higher-order structure of DNA, e.g. nucleosomes and chromatin.     

The Realization of Large-Scale Photonic Integrated Circuits and the Associated Impact on Fiber-Optic Communication Systems

Large-scale photonic integrated circuits (LS PICs) have been extensively deployed throughout the fiber optic communication network. This paper discusses the properties of the LS PICs, the interaction between them, and what is necessary to create an optical transport system that fully utilizes the properties of the LS PIC     

Basic aspects concerning the event-synchronous interference canceller

The adaptive noise canceller (ANC) is a commonly used linear system method for noise reduction in cases where the disturbing noise can be separately recorded (reference signal) and is not correlated with the signal of interest. In case of a periodic disturbing signal, special solutions are described in literature. Problems, however, arise when the propagation of the noise from the source to the recording sensors passes nonlinear structures. An ANC modification proposed for this case by Strobach et al. and applied by several other researchers, thus, uses an artificial reference signal, based on event triggered averaging of segments of the recorded wanted (but disturbed) signal in order to obtain a template for the repetitive distortion sequence and to construct the artificial reference signal. The effect of the averaging and the error introduced by this approximation of the real disturbing signal was not addressed in literature until now, thus, this paper presents some basic theoretical considerations on this topic. Methods are demonstrated in simulations and real biosignal processing, and application aspects are discussed.     

Adaptive Noise Cancellation Techniques in Sigma–Delta Analog-to-Digital Converters

Adaptive noise cancellation (ANC) techniques that extract a desired signal from background noise have many applications in different engineering disciplines. In ANC, the corrupted signal is passed through a filter that tends to suppress the noise while leaving the original signal unchanged. This paper demonstrates that the adaptive noise cancellation technique can be embedded in the digital signal postprocessing of a sigma-delta analog-to-digital converter and effectively reduces the quantization noise as well as the thermal noise at the output of the converter. The combination of ANC and the noise-shaping technique enable high-resolution analog-to-digital conversion in wideband applications where noise shaping alone cannot provide enough suppression of quantization noise due to the low oversampling ratio.     

Least-squares model order reduction enhancements

Two enhancements to the least-squares (LS) discrete-time model order reduction (MOR) method are presented: scaling and frequency response matching. Scaling generally improves the low-frequency fit between the reduced-order model (ROM) and the original model. For exact gains at specific frequencies, optional frequency response constraints can easily be added to the LS MOR method. An example is presented that illustrates these enhancements. The example model is reduced with the Hankel norm, weighted impulse response gramian, and LS MOR methods. Plots of error versus frequency are given for each of the three MOR methods