Picosecond pulse propagation on coplanar striplines fabricated onlossy semiconductor substrates: modeling and experiments

A simple model for the propagation of high-frequency signals on coplanar striplines with lossy semiconductor substrates is proposed and demonstrated. This model incorporates the effect of a conductive substrate through the loss tangent in a distributed-circuit analysis extended to high frequencies. Very strong attenuation and dispersion due to the substrate are observed even when the GaAs conductance is only 1 mho/cm, corresponding to a doping density of around 10¹⁵ cm ^-3. The accuracy of this model is tested with a direct comparison to experimental data of picosecond pulse propagation on a doped GaAs coplanar stripline (CPS) measured in the time domain using the electro-optic (EO) sampling technique. Good agreement is found in terms of the attenuation and phase velocity of the distorted pulses at four propagation distances up to 300 μm. The pulse propagation on a multiple modulation-doped layer is also studied experimentally as a prototype of high-frequency signal propagation on the gate of a modulation-doped field-effect transistor (MODFET). The attenuation shows linear frequency dependence up to 1.0 THz, contrary to the cubic or quadratic dependence of coplanar transmission lines on low-loss substrates     

A QRS-complex detector of the electrocardiogram signal for the long-term monitoring of the patient’s condition

A procedure for detection of the QRS complexes of electrocardiogram (ECG) signals for systems of long-term monitoring of the patient’s condition based on successive use of the band-pass filtering, the Hilbert transform, and an adaptive threshold algorithm is considered. The efficiency of different QRS-complex detectors has been investigated for model ECG signals in the presence of interferences of various nature and intensity. The efficiency of the proposed procedure has been additionally tested using various clinic records of ECG signals from the MIT Physionet database.     

Variability of the QRS signal in high-resolution electrocardiograms and magnetocardiograms

The variability of electric and magnetic signals from the heart during the depolarization phase is investigated. A signal processing method is developed, which provides estimates for the beat-to-beat variability of the QRS-complex. The method is based on the decomposition of the depolarization signal into bandpass signals by means of the Morlet wavelet transform. The beat variability of the depolarization signal is estimated by normalized variances of the envelope and instantaneous frequency of bandpass signals. Time intervals of the bandpass filtered depolarization signals having a high signal-to-noise ratio are selected applying an analysis based on phase statistics. The method was tested by computer simulation and experimental data taken from electrocardiographic and magnetocardiographic measurements of healthy persons and patients prone to malignant ventricular tachycardia (VT) or ventricular fibrillation (VF). Results suggest that the calculated variance parameters permit the characterization of beat variable depolarization signals and distinguish VT/VF patients from healthy persons.     

基于小波分析的迎角传感器信号预处理

针对基于四象限压力传感器阵列的迎角测量方法中,传感器信号受到干扰的问题,讨论了在其预处理中应用小波变换进行信号分离提取的方法.根据小波分解理论,对信号进行多尺度的小波变换,信号中频率不同的部分落在不同的尺度上,剔除反映干扰的小波变换尺度,提取出有用信息.结果表明,该方法可较好地提取信号的主要特征信息,有效的去除了确定性干扰和随机噪声,与传统的信号滤波方法相比较具有明显的优点,同时为后续的信号处理奠定了基础.     

Low bit rate transparent audio compression using adapted wavelets

Describes a novel wavelet based audio synthesis and coding method. The method uses optimal adaptive wavelet selection and wavelet coefficients quantization procedures together with a dynamic dictionary approach. The adaptive wavelet transform selection and transform coefficient bit allocation procedures are designed to take advantage of the masking effect in human hearing. They minimize the number of bits required to represent each frame of audio material at a fixed distortion level. The dynamic dictionary greatly reduces statistical redundancies in the audio source. Experiments indicate that the proposed adaptive wavelet selection procedure by itself can achieve almost transparent coding of monophonic compact disk (CD) quality signals (sampled at 44.1 kHz) at bit rates of 64-70 kilobits per second (kb/s). The combined adaptive wavelet selection and dynamic dictionary coding procedures achieve almost transparent coding of monophonic CD quality signals at bit rates of 48-66 kb/s     

Peak transform for efficient image representation and coding.

In this work, we introduce a nonlinear geometric transform, called peak transform (PT), for efficient image representation and coding. The proposed PT is able to convert high-frequency signals into low-frequency ones, making them much easier to be compressed. Coupled with wavelet transform and subband decomposition, the PT is able to significantly reduce signal energy in high-frequency subbands and achieve a significant transform coding gain. This has important applications in efficient data representation and compression. To maximize the transform coding gain, we develop a dynamic programming solution for optimum PT design. Based on PT, we design an image encoder, called the PT encoder, for efficient image compression. Our extensive experimental results demonstrate that, in wavelet-based subband decomposition, the signal energy in high-frequency subbands can be reduced by up to 60% if a PT is applied. The PT image encoder outperforms state-of-the-art JPEG2000 and H.264 (INTRA) encoders by up to 2-3 dB in peak signal-to-noise ratio (PSNR), especially for images with a significant amount of high-frequency components. Our experimental results also show that the proposed PT is able to efficiently capture and preserve high-frequency image features (e.g., edges) and yields significantly improved visual quality. We believe that the concept explored in this work, designing a nonlinear transform to convert hard-to-compress signals into easy ones, is very useful. We hope this work would motivate more research work along this direction.     

Theoretical performance limits on tropospheric refractivityestimation using point-to-point microwave measurements

Ducted propagation above the ocean surface can seriously impact shipboard radar and communications. Point-to-point microwave measurements have been proposed as a means of estimating tropospheric refractivity for the purposes of characterizing surface-based ducts. This paper addresses the theoretical performance of refractivity estimates that can be made by combining field measurements at different frequencies with prior statistics of refractivity variation. Parameterizing the refractivity profile using empirical orthogonal functions derived from a historical database, both Cramer-Rao performance bounds and the maximum a posteriori (MAP) estimate are discussed using coherent or incoherent signals. Results obtained using a realistic model of refractivity conditions off Southern California suggest that multifrequency propagation measurements can significantly improve the estimation of refractivity and propagation loss profiles     

基于小波变换的中红外多波长辐射测温的信号处理

介绍了用小波变换实现中红外多波长辐射测温信号的处理方法，该方法基于信号和白噪声在小波变换下具有不同的传播特性，采用软阈值方法有效地去除信号中的噪声，方便地用软件实现辐射测温信号的处理。为将小波变换引入辐射测温领域进行了探讨。     

基于低速采样的多正弦波信号频率估计

高频段信号由于受到A/D转换器和后续信号处理器件运算速度和成本的限制,其处理往往难以实现,为解决此问题,提出了一种新的基于低速采样的高频段多正弦波信号频率估计方法。首先将含有多个频率互异的多正弦波信号经过功分器分成两路信号,然后分别用不同的采样率对这两路信号进行低速采样,用傅立叶变换及基于改进的Rife算法与Quinn算法来估计两路信号低速采样后的频率,接下来利用中国余数定理对多个信号的频谱快速配对解模糊准确的估计出各个信号的频率。该方法在工程上易于实现,可同时实现低的采样速率与高精度估计,而且在较低信噪比的情况下仍可获得较高的估计精度。给出了该方法的具体步骤,通过计算机仿真试验验证了该方法的有效性。      

小波变换在光谱特征提取方面的应用

人们在处理高光谱图像时一般要对一些典型地物进行光谱分析、特征波段的提取,以便提取出最大量的有效信息,剔除无用或冗余的信息,然后再进行分类识别.采用小波变换的分析方法,选用合适的小波进行分解,根据分解后的高频分量中包含的重要信息,利用局部相邻的正负极值点找出对应于原始光谱曲线上每个吸收带的左右边界;利用局部过零点,即可比较精确的提取出各个吸收带的中心波长.该方法比传统的光谱特征提取方法更简洁、有效,实验证明为一种比较理想的光谱特征提取方法.     

The Role of Slow Potassium Current in Nerve Conduction Block Induced by High-Frequency Biphasic Electrical Current

The role of slow potassium current in nerve conduction block induced by high-frequency biphasic electrical current was analyzed using a lumped circuit model of a myelinated axon based on the Schwarz–Reid–Bostock model. The results indicate that nerve conduction block at stimulation frequencies above 4 kHz is due to constant activation of both fast and slow potassium channels, but the block at stimulation frequencies below 4 kHz could be due to either anodal or cathodal dc block depending on the time of the action potiential arriving at the block electrode. When stimulation frequency was above 4 kHz, the slow potassium current was about 3.5 to 6.5 times greater than the fast potassium current at blocking threshold, indicating that the slow potassium current played a more dominant role than the fast potassium current. The blocking location moved from the node under the blocking electrode to a nearby node as the stimulation intensity increased. This simulation study reveals that in mammalian myelinated axons, the slow potassium current probably plays a critical role in the nerve conduction block induced by high-frequency biphasic electrical current.      

高频小信号谐振放大电路时域与频域对比分析

高频小信号谐振放大电路,主要是用来放大采集的微小的高频电压信号,但是放大器的负载不是线性电阻而是具有选频功能的谐振网络。所以谐振放大电路能够对不同频率的信号进行不同增益的放大,在信号的选择等方面具有重要的作用。文章从时域以及频域两个方面对谐振放大电路进行对比分析。     

The single nerve fiber action potential and the filter bank--a modeling approach

Single fiber action potentials (SFAPs) from peripheral nerves, such as recorded with cuff electrodes, can be modelled as the convolution of a source current and a weight function that describes the recording electrodes and the surrounding medium. It is shown that for cuff electrodes, the weight function is linearly scaled with the action potential (AP) velocity and that it is, therefore, possible to implement a model of the recorded SFAPs based on a wavelet multiresolution technique (filterbank), where the wavelet scale is proportional to the AP velocity. The model resulted in single fiber action potentials matching the results from other models with a goodness of fit exceeding 0.99. This formulation of the SFAP may serve as a basis for model-based wavelet analysis and for advanced cuff design.     

Dominant frequency analysis of EEG reveals brain's response duringinjury and recovery

A new method of monitoring and analyzing electroencephalogram (EEG) signals during brain injury is presented, EEG signals are modeled using the autoregressive (AR) technique to obtain the frequencies where there are peaks in the spectrum. The powers at these dominant frequencies are analyzed to reveal the state of brain injury during an experimental study involving progressive hypoxia, asphyxia, and recovery. Neonatal piglets (n=8) were exposed to a sequence of 30 min of hypoxia (10% oxygen), 5 min of room air, and 7 min of asphyxia. They then received cardiopulmonary resuscitation and were subsequently monitored for 4 h. An optimal AR model order of 6 was obtained for these data, resulting in 3 dominant frequencies. These dominant frequencies, referred to as the low, medium, and high frequency components, fell in the bands 1.0-5.5 Hz, 9.0-14.0 Hz, and 18.0-21.0 Hz, respectively. A remarkable feature of the authors' data is the spectral dispersion, or diverging trends in the 3 frequency bands. During hypoxia, the relative powers of the medium and high-frequency components of EEG increased up to 160% and 176%, from their respective baseline values. During the first minute of asphyxia the medium- and high-frequency powers (relative to baseline) increased by 280-400%. The power in all 3 frequency components went down to nearly zero within 40-80 s of asphyxia. During recovery, the phenomenon of burst-suppression was clearly exhibited in the low-frequency component. A new index, called mean normalized separation, representing the degree of disproportionality in the recovery of powers of the 3 dominant components relative to their mean recovered power, is presented as a possible single indicator of electrical function recovery. In conclusion, dominant frequency analysis helps reveal the brain's graded electrical response to injury and recovery     

Slow fading cross-correlation against azimuth separation of basestations

A model is proposed to describe the cross-correlation of slow fading signals received from non-colocated base stations. The model summarises the results obtained from a bootstrap analysis of 900 MHz urban area propagation measurements     

基于经验模态分解的激光干涉信号处理

为了去除激光干涉测速系统提取的小波脊的大量高频噪声,提高系统测量精度,采用一种基于经验模态分解的小波脊优化的方法,对高频噪声强度进行了很好的抑制,测量误差为原来未优化误差的42.3%,较大幅度提高了激光干涉测速系统的测量精度.结果表明,该方法对经过时频分析的信号去噪有重要的实用价值.     

Coplanar transmission lines on thin substrates for high-speedlow-loss propagation

We investigate the attenuation and phase velocity characteristics of coplanar strip (CPS) transmission lines designed for high-speed, low-loss propagation at sub-THz frequencies. Photoconductor switches driven by femtosecond optical pulses were used to generate propagating picosecond electrical transients. External electrooptic sampling was used to measure the time-domain impulse-response characteristics with subpicosecond time resolution. The finite-difference transmission-line-matrix (FD-TLM) numerical method was used to model picosecond pulse propagation on identical transmission lines. The experiment and the numeric simulations have clarified nonquasistatic high-frequency effects and were shown to agree over a 500 GHz frequency range. Additionally, analytic quasi-static velocity and characteristic impedance formulas have been verified and their frequency range of validity established for the investigated CPS geometries. Radiation into the substrate is the dominant loss mechanism at frequencies above ~100 GHz for the CPS lines on thick substrates. CPS transmission line fabrication on thin substrates has been proposed as a method for reducing high-frequency loss and increasing the microwave propagation velocity. CPS transmission lines fabricated on 8-μm-thick Si membranes have been studied and demonstrated to possess the desired high-speed, low-loss properties     

基于Morlet小波的水下声信号频率识别

为准确获取水下目标的发声频率,建立了激光干涉法探测水下声信号的实验系统。提出一种基于Morlet小波的水声信号处理方法,将Morlet小波母函数的频率取定值,改变尺度因子,利用两者比值与水下声信号频率的关系分析小波系数模值,实时获取水下声信号的频率信息。实验结果表明:小波系数图可以反映出水下目标在某一时刻的发声频率,实验系统能够实时探测出1～15kHz的水下声信号。     

Blind separation of slow waves and spikes from gastrointestinalmyoelectrical recordings

Myoelectrical recordings of the gut contain slow waves (slow rhythmicity) and spikes (fast rhythmicity). While the slow wave determines the frequency and propagation of gastrointestinal contractions, spike activities are directly associated with the contractions. Traditionally, spikes are extracted from the myoelectrical recording using high-pass/bandpass filters. Due to the sharp rising edge (high-frequency component) of the slow wave, the conventional method is not accurate in the separation of the slow wave and spikes, although it has been used for years. In this paper, a novel and fast blind source separation algorithm is developed. Experimental results show that the proposed method was able to accurately extract spike activities from the myoelectrical recordings obtained in dogs and that its performance was not affected by the high-frequency components of the slow wave     

基于时频脊线的跳频参数盲估计

 为了估计未知跳频信号的参数,提出一种基于时频脊线的跳频参数盲估计方法,根据跳频信号频率的瞬变特性,通过对跳频信号时频脊线的小波变换,可以准确估计跳周期,进而估计其它跳频参数.理论分析和仿真结果表明,该方法可以在低信噪比下以较低的运算复杂度实现高精度的参数估计,整体性能优于现有的跳频参数盲估计方法.