Output SNR Research Articles

A Broadband Resonant Noise Matching Technique for Piezoelectric Ultrasound Transducers

A novel resonant noise matching technique is proposed to improve the sensitivity and output SNR of ultrasound receivers. Diverse from the power matching, the resonant noise matching technique proposed in this paper applies resonant LC networks to raise the transducers’ input impedance to a high impedance. As a consequence, in addition to the function of improving the output signal strength, the prominent advantage of the resonant noise matching technique is that the passive gain provided by the matching network can reduce equivalently the receiver’s input-referred noise and thus obtain the minimum noise figure. Furthermore, broadband matching which can cover the transducers’ working bandwidth is also developed to reduce the ringing in received signals, which can significantly improve axial resolution in applications of imaging. For this, an accurate electrical model extended from Butterworth Van-Dyke (BVD) model is obtained to co-simulate with the new matching network in the design. Measurement results show that, the output signal is improved by 5 times through the proposed technique, which is 66.7% larger than that of conventional methods. In addition, the sensitivity of the receiver is significantly improved by more than 10.4 dB which is beneficial for piezoelectric ultrasound transducers in a variety of applications.

Anti-interference Algorithm for Broadband Wireless Communication based on Embedded Microcontroller

In order to improve the reliability of broadband wireless communication, the anti-interference design of broadband wireless communication in embedded environment is carried out, and an anti-interference algorithm of broadband wireless communication based on embedded microcontroller is proposed. The hardware of the anti-interference device is mainly composed of the communication modulating module, ARM main control system module and the single chip microcomputer main control module. The anti-interference algorithm is designed by using inter-symbol interference suppression algorithm, and the data transmission channel distribution model of broadband wireless communication is constructed. The interference filtering of broadband wireless communication is based on the decision feedback equalization method. The simulation results show that the anti-interference design of broadband wireless communication using this method has strong anti-interference ability, the output SNR is higher than that of the traditional method, and the communication quality is improved.

Performance analysis of a DCO-CO-OFDM optical transmission system with distributed Raman amplifier using coherent heterodyne receiver

A novel analytical approach is developed to evaluate the bit error rate performance (BER) of a DC biased optical coherent orthogonal frequency division multiplexing (DCO−CO-OFDM) transmission system with distributed Raman amplifier using single mode fiber (SMF) considering intensity modulation and coherent heterodyne detection. Analytical expressions are developed for optical SNR (OSNR) at the output of the fiber link along with IF-SNR and output SNR to evaluate the conditional BER performance for a given output of DCO-OFDM demodulator. Average BER is evaluated by averaging the conditional BER over the pdf of the output of DCO-OFDM demodulator. Results are evaluated in terms of average BER with different systems parameter viz. input signal power, pump power, local oscillator power, modulation index, number of OFDM sub-channel, fiber length and data rate. Results show that DCO−CO-OFDM optical transmission system offers better performance compared to CO-OFDM optical transmission reported earlier. It is further noticed that performance of an optical OFDM transmission link can be significantly improved by increasing the number of OFDM subcarrier and DC bias level. The results are found to be in conformity with the results of CO-OFDM reported earlier.

Fast recognition method of text features in dynamic video images

In order to improve the text recognition ability of dynamic video image, a fast text feature recognition method based on block area contour detection is proposed. The fuzzy video feature analysis method is used to collect the text features of the dynamic video image, reorganise the frame structure, and extract the edge features of the text features of the image. The collected text features are fused into multi-dimensional information, and the edge contour feature information of dynamic video image is matched by block matching method. In this paper, a packet fusion model of Chinese text feature in dynamic video image is established, and the corner detection of text feature is carried out by surf algorithm to realise the fast recognition of Chinese text feature in dynamic video image. Simulation results show that the maximum SNR of the image text feature recognition output is 44.8 dB, and the recognition accuracy is high.

CSI-Independent Non-Linear Signal Detection in Molecular Communications

Molecular communications rely on diffusive propagation to transport information, which is attractive for a variety of nano-scale applications. Due to the long-tail channel response, spatial-temporal coding of information may lead to severe inter-symbol interference (ISI). Classical linear signal processing in wireless communications is usually operating with high complexity and high signal-to-noise ratios, whereas signal processing in molecular communication system requires operating in opposite conditions. In this work, we propose a novel signal processing paradigm inspired by the biological principle, which enables low-complexity signal detection in extremely noisy environments. We first propose a non-linear filter inspired by stochastic resonance, which is found in a variety of biological systems, and it can significantly improve the output SNR by converting noise to useful signals. Then, we design a non-coherent detection method, one which exploits the generally transient trend of observed signals (i.e. quick-rising and slow-decaying) rather than hidden channel state information (CSI), thus excluding CSI estimation and involving only summations. Implementation issues are also discussed, including parameters configuration and adaptive threshold. Numerical results show that the proposed bio-inspired scheme can improve the performance remarkably over classical approaches. Even compared with the optimal linear methods, the required SNR of the proposed scheme can be reduced by 7 dB, which reaffirms why it can be used in noisy biological environments. As the first attempt to design bio-inspired molecular signal detectors, the proposed non-linear processing paradigm may provide the great promise to the emerging nano-machine applications.

A novel approach adaptive filtering method for electromyogram signal using Gray Wolf optimization algorithm

The proposed paper, presents the construction of adaptive noise cancellation filter based on gray wolf optimization (GWO) optimization technique.The relative investigation of different strategies uncovers that the presentation of GWO calculation is better in boisterous condition. The objective of proposed paper is structure ANC channel utilizing GWO method that improves association involving output with pure EMG signal.The results of proposed strategy are contrasted through gray wolf optimizer (GWO) and other evolutionary algorithms.The presentation of these calculations is assessed regarding signal-to-noise ratio (SSNR), mean square error (SMSE), maximum error (SME) mean, convergence rate (CR) plus correlation feature (Sr). The noise attenuation capability is tested on EMG signal contaminated with power line and ECG noise at different SNR levels. The ANC filter based on GWO technique provides 28 dB improvement in output SNR, 81% reduction in MSE, and 84% lower ME as compared to reported ANC filter based on RLS algorithm. Further, ANC filter based on GWO technique provides 7 dB improvement in output SNR, 59.5% reduction in MSE, and 69.2% lower ME as compared to recently reported ANC filter based on ABC-MR algorithm.

Performance Study of Wireless Systems with Switch and Stay Combining Diversity over α-η-μ Fading Channels

In this paper, we consider a Switch and Stay Combiner (SSC) diversity scheme operating over α−η−μ fading channel. New and closed-form expressions for the average output SNR (ASNR), the moment-generating function (MGF), the outage probability (P_out), and the average symbol error rate (ASER) for M-ary quadrature amplitude modulation (QAM) signaling are derived. The expressions are obtained in terms of the well-known bivariate Fox’s H-function (BFHF). It is worth pointing out that the BFHF and the bivariate Meijer’s G-function (BMGF) have recently been used extensively in wireless communications literature to study the system's performance. The evaluated results are plotted for channel parameters of interest, and the effect of fading severity on the combiner performance is studied. Moreover, the results are shown to match those previously reported in the literature for other channel models such as η−μ as a special case, which confirms the validity of the obtained expressions. Also, insights on the optimal choice of the switching threshold are provided.

A Calibration-Free 12-bit 50-MS/s Full-Analog SAR ADC With Feedback Zero-Crossing Detectors

This paper presents a calibration-free 12-bit 50-MS/s full-analog SAR analog-to-digital (A-to-D) converter (ADC) in 40-nm CMOS, which integrates the functions of comparator, SAR logic, and digital-to-analog converter (DAC) switches into multiple feedback zero-crossing detectors (FB-ZCDs). By eliminating all the digital circuits, the full-analog bit conversions operate with the asynchronous amplification-to-regeneration (A-to-R) operation that highly relaxes the requirements of the analog circuits and reference generator. This paper is implemented without any calibration, where the non-ideal effects (offset mismatch, insufficient residue, and noise) are mitigated and eliminated with the proposed techniques as follows. The offset mismatches among the FB-ZCDs are covered by the redundancies of the sub-radix DAC arrangement in the coarse ADC. The bottom-plate coupling compensators (BPCCs) are proposed to correct the consecutive SAR decision errors as quantizing the insufficient residue. The shared FB-ZCD with capacitor coupling decision (CCD) network is developed to obtain the identical offset in the fine ADC. Amplification extension (AE) technique is proposed to enhance the precision of the shared FB-ZCD by reconfiguring as a complementary inverter-based amplifier with the extended amplification period to enhance the output SNR. This paper occupies an active area of 0.01 mm2 and achieves the Nyquist-rate signal-to-noise-and-distortion ratio (SNDR), spurious-free dynamic range (SFDR), Walden figure-of-merit (FoMW), and Schreier FoM (FoMS) of 64.1, 75.6 dB, 5.3 fJ/conversion step, and 172.8 dB, respectively.

Acoustic feedback cancellation in hearing aids using dual adaptive filtering and gain-controlled probe signal

In this paper, we propose a probe signal-based adaptive filtering method for acoustic feedback cancellation (AFC) in hearing aids. The proposed method consists of two adaptive filters. The first adaptive filter is excited by the receiver (loudspeaker) signal, and uses the microphone signal as its desired response. The first adaptive filter shows a fast convergence speed, however, it may converge to a biased solution at the steady-state because its input and desired response are correlated with each other. The second adaptive filter is excited by an internally generated (uncorrelated) probe signal. The two adaptive filters are adapted using a delay-based normalized least mean square (NLMS) algorithm. A strategy is devised to exchange the coefficients of two adaptive filters such that the both adaptive filters give a good (unbiased) estimate of the acoustic feedback path. Furthermore, we propose to vary the gain of the probe signal, such that a high level probe signal is injected during the transient state, and a low level probe signal is used after the AFC system has converged. The computer simulations demonstrate that the proposed method achieves good modeling accuracy, preserves good speech quality, and maintains high output SNR at the steady-state.

Adaptive Artifact Cancelation Based on Bacteria Foraging Optimization for ECG Signal

In this paper, the design of adaptive artifact canceler (AAC) filter using bacteria foraging optimization (BFO) algorithm is presented. The performance of proposed AAC filter is tested on a corrupted ECG signal. Based on simulation results, it is observed that the AAC filter designed with BFO technique achieves significant improvement in fidelity parameters such as SNR, NRMSE, and NRME when compared with other reported algorithms in the literature. AAC filter based on BFO technique provides 6 dB improvement in output SNR, 85% reduction in NRMSE, and 90% lower NRME as compared to recently reported AAC filter based on ABC-SF algorithm. Further, AAC filter using BFO technique enhances the coherence between pure and reconstructed ECG signals.

Infrared gas detection technology based on parameter-tuning stochastic resonance

When infrared gas detection technology is applied to monitor gases, the detection accuracy decreases due to the influence of systematic noise. The noises are filtered using traditional denoising methods; however, these methods affect the useful signal. An infrared photoelectric signal is analyzed using the parameter-tuning stochastic resonance method. Based on the parameter normalization frequency and the output SNR tuning bistable system parameters, the system reaches the optimal resonance state, and the signal after denoising is obtained using the Runge–Kutta algorithm. The numerical simulation is conducted on the periodic photoelectric signal with input SNR of 10 dB. It is determined that the method is suitable for the photoelectric signal detection with a frequency from 1 to 10 Hz and that the output SNR is increased to 20 dB in the optimal resonance state. The comparison experiment results show that this method can improve the original signal more effectively than other denoising methods, improving the SNR to 25 dB. In the CO2 standard gas concentration range of 0% to 5%, the maximum relative error of inversion is ±7 % , and the correlation between the inversion result and the standard concentration is 0.9982. This suggests that the proposed method is effective for infrared photoelectric signal detection under strong noise conditions.

Stochastic Resonance in Unsaturated Piecewise Nonlinear Bistable System Under Multiplicative and Additive Noise for Bearing Fault Diagnosis

With regard to the fault diagnosis, the stochastic resonance (SR) method takes advantage of noise imbedded in vibration signals while most traditional methods suppress or eliminate noise to enhance weak fault characteristics. In this paper, a novel piecewise nonlinear bistable SR (PNBSR) is proposed and its corresponding potential function called piecewise nonlinear bistable system (PNBS) overcomes the output saturation disadvantage which bothers the classical bistable system (CBS). The output saturation limits the enhancement capability for extracting fault characteristics of classical bistable SR (CBSR). Satisfying the adiabatic condition, the expression of the output signal-to-noise (SNR) of PNBSR is derived and compared with the output SNR of CBSR. Considered the multiplicative and additive noise, two methods are applied to extract characteristic frequency from simulated harmonic vibration signal and actual bearing fault signals. The SNR increase (SNRI) is chosen as the index for evaluating the performance of CBSR and PNBSR in experimental simulations. The diagnosis results indicate that the proposed PNBSR method is superior to the CBSR by analyzing SNRI and the effect of extracting fault characteristics.

A chemogenetic approach for treating experimental Parkinson's disease.

PD is a common neurodegenerative disease primarily affecting the cortico-basal ganglia loop. To investigate whether chemogenetic-mediated neuromodulation of various nuclei and pathways can counterbalance basal ganglia network abnormalities and improve motor disability in experimental PD. Experimental PD was induced by stereotactic injection of 6-OHDA to the medial forebrain bundle. Designer receptors exclusively activated by designer drugs were expressed in different basal ganglia nuclei by stereotactic injections of adeno-associated viral vectors. We compared motor performance, monitored by the open-field and rotarod tests, after random and blinded application of either normal saline or the synthetic receptor activator, clozapine-N-oxide. Motor performance, as measured by movement velocity, rotations, and rotarod scores, were significantly improved in PD mice by enhancing the activity of the GPe with Gq custom receptors and by reducing basal ganglia output activity, targeting the output nuclei GPi and SNr with Gi custom receptors. Our findings support the hypothesis that enhanced inhibitory output activity of the basal ganglia complex underlie motor signs in PD, and point to the therapeutic potential of chemogenetic based treatments in PD patients. © 2018 International Parkinson and Movement Disorder Society.

Stochastic resonance in two kinds of asymmetric nonlinear systems with time-delayed feedback and subject to additive colored noise

This paper attempts to investigate the stochastic resonance (SR) behaviors in two kinds of asymmetric nonlinear systems with time-delayed feedback driven by additive colored noise by virtue of two-state theory, small time delay approximation, path integral approach, and unified colored-noise approximation, where asymmetric nonlinear systems include asymmetric well depth and asymmetric well width alone. The characteristics of SR in two kinds of asymmetric systems are different for different asymmetric ratios and correlated times of additive colored noise. For asymmetric well width, optimal noise intensity is independent of asymmetric ratio and correlated time, whereas for asymmetric well depth it is closely related with asymmetric ratio and correlated time. However, optimal noise intensity is closely related with feedback intensity, and time-delay for two kinds of asymmetries. Even there exists the optimal feedback intensity, time delay and correlated time to make output SNR maximum. Above clues are helpful to achieve weak signal detection under strong background noise.

An Improved Bi-Level Thresholding Based Uncertainty Evaluation for Speech Enhancement in Non-Stationary Noises

This paper proposes a new speech enhancement framework to improve the quality of speeches recorded under adverse acoustic environments based on the speech presence uncertainty. Since the uncertainty evaluation gives a more and clear discrimination about the speech and noise, this paper proposes a new uncertainty evaluation mechanism as a preprocessing mechanism to the noise suppression methods. This mechanism relates with energies of a noisy speech signal and classifies the speech segments and noise segments more perfectly. In addition to the quality enhancement, this approach also reduces the unnecessary computational burden over the speech processing system. Extensive simulations are carried out over the speech signals with different types of non-stationary noises like babble noise, exhibition noise, restaurant noise and train station noises and the performance is measured with the performance metrics namely the Output SNR, AvgSegSNR, PESQ and COMP. The comparative analysis of proposed approach over the conventional approaches shows an outstanding performance in all environments.

Online approximation of the multichannel Wiener filter with preservation of interaural level difference for binaural hearing-aids

This work presents an online approximation method for the multichannel Wiener filter (MWF) noise reduction technique with preservation of the noise interaural level difference (ILD) for binaural hearing-aids. The steepest descent method is applied to a previously proposed MWF-ILD cost function to both approximate the optimal linear estimator of the desired speech and keep the subjective perception of the original acoustic scenario. The computational cost of the resulting algorithm is estimated in terms of multiply and accumulate operations, whose number can be controlled by setting the number of iterations at each time frame. Simulation results for the particular case of one speech and one-directional noise source show that the proposed method increases the signal-to-noise ratio SNR of the originally acquired speech by up to 16.9 dB in the assessed scenarios. As compared to the online implementation of the conventional MWF technique, the proposed technique provides a reduction of up to 7 dB in the noise ILD error at the price of a reduction of up 3 dB in the output SNR. Subjective experiments with volunteers complement these objective measures with psychoacoustic results, which corroborate the expected spatial preservation of the original acoustic scenario. The proposed method allows practical online implementation of the MWF-ILD noise reduction technique under constrained computational resources. Predicted SNR improvements from 12 dB to 16.9 dB can be obtained in application-specific integrated circuits for hearing-aids and state-of-the-art digital signal processors.

A Robust Translational Motion Compensation Method for ISAR Imaging Based on Keystone Transform and Fractional Fourier Transform Under Low SNR Environment

In this work, a parametric-based approach is proposed to perform joint range alignment and phase adjustment based on the intention of fully exploiting the energy of all the scatterers in the moving target and the two-dimensional coherent accumulation gain of both range and azimuth compressions. To that end, first, translational motion is modeled as a polynomial signal, and inspired by the fact that all the scatterers in the moving target experience the same translational range history, the phase difference operation and keystone transform (KT) are utilized to transform the energy of all the scatterers into one range cell. Second, by the virtue of the fractional Fourier transform (FrFT), the energy of all the scatterers is coherently accumulated into a peak point, and from which the polynomial coefficients can be obtained accurately. With the estimated polynomial coefficients, the dechirp operation and KT are applied jointly to compensate range misalignment and phase error. The analysis of the proposed method shows that it is of low computational complexity due to avoiding multidimensional search and improves the output SNR providing satisfactory low SNR performance. The experimental results are provided to demonstrate the performance of the proposed method compared with the state-of-the-art algorithms.

Stochastic Resonance in an Array of Dynamical Saturating Nonlinearity with Second-Order

The transmission of weak noisy signal by parallel array of dynamical saturating nonlinearities with second-order is studied. Firstly, the numerical results demonstrate that the output SNR can be enhanced by parallel array of dynamical saturating nonlinearities with second-order by tuning the internal noise. Secondly, the SR effects can be optimized by the self-coupling coefficient of the dynamical nonlinearity. Then, the SR effects when the non-Gaussian noise acts as the external noise are superior to that with external Gaussian noise.

Signal Degradation and Excess Insertion Loss of Optical Mach–Zehnder Modulators in the Presence of Electronic Dispersion Compensation

Mach-Zehnder (MZ) modulators are widely used in optical transmitters to generate high-speed optical signals. With electronic dispersion compensation (EDC), the driving signals to MZ modulators change from digital to analog, or continuous waveforms. Consequently, there is signal degradation from their sinusoidal transfer curves. In this paper, we theoretically and numerically investigate the signal degradation in optical transmitters using MZ modulators in the presence of EDC. We show that the temporal waveforms follow the Gaussian distribution when the EDC is large, and therefore, the modulation index needs to be optimized between the output SNR and the excess insertion loss of MZ modulators. With varying modulation index, we quantify the output SNR and excess insertion loss of optical IQ modulators that consist of two parallel MZ modulators. The calculations are also extended to the scenarios where the sinusoidal transfer curves are compensated for. All the analytical results are verified in a simulation of QPSK transmissions, and they are useful for finding an optimized modulation index for a tradeoff between the output SNR and excess insertion loss.

COMPRESSIVE SENSING BASED SIGNAL RECOVERY WITH DIFFERENT TRANSFORMS

Compressive sensing (CS) is a new technique that give an approach to reconstruct the signal with few numbers of observations or measurements. The CS is based on L1 -norm minimizations to find the sparse solutions and it is known as basis pursuit. In this investigation, CS scheme with different transforms is proposed. The three utilized transform techniques are: Discrete Fourier Transform(DFT), Discrete Cosine Transform(DCT) and Discrete Wavelet Transform(DWT) with daubechies1(DB1) and coiflets1(coif1) basis. The proposed system is tested by employing the following signals: Blocks, Heavy Sine, ‘Bumps’ and ‘Doppler’ which cover wide range of applications. The four testing signals are represented in sparse domain using different transforms. In order to threshold the coefficients of the signals in sparse domain, the universal threshold is utilized in the case of CS with FFT and DWT whereas, the universal threshold is modified to prune the DCT coefficients. The main aim of this study is to investigate the differences among CS with DFT, CS with DCT and CS with DWT, and consequently a suitable transform domain used with CS to be selected. The comparative study is established by assessing the performance of the proposed system using Root Mean Square Error (RMSE), output SNR, and the time required to reconstruct approximated signals. Simulation results have shown that the CS with DWT outperforms the CS with FFT and DCT. CS with DWT has achieved good RMSE values about (0.0014 to 3.359e-8) even when half of the signal elements are removed. CS with FFT and DCT enhanced the noisy Blocks and Bumps signals by 3dB and 1dB respectively, while it is failed to enhance noisy Heavy Sine and Doppler signals. CS with DWT of two basis and for single decomposition level have improved the noisy Blocks, Bumps, Heavy Sine and Doppler signals by 5dB, 4dB, 3dB, and 3dB respectively.