Problem Of Nonlinear Distortion Research Articles

A Simplified Volterra Equalizer Based on System Characteristics for Direct Modulation Laser (DML)-Based Intensity Modulation and Direct Detection (IM/DD) Transmission Systems

The nonlinear Volterra equalizer has been proved to be able to solve the problem of nonlinear distortion, but it has high computational complexity and is difficult to implement. In this paper, a simplified second-order Volterra nonlinear equalizer designed for intensity modulation/direct detection systems based on direct modulated laser is proposed and demonstrated, taking into account the characteristics of the system. It has been proved that the received signal of direct modulation laser/direct detection system can be expressed in Volterra series form, but its form is too complex, and the device parameters should also be considered. We re-derived it and obtained a more concise form. At the same time, we proposed a method to simplify the second-order Volterra nonlinear equalizer without relying on device parameters. The performance of the proposed Volterra nonlinear equalizer is evaluated experimentally on a 56 Gb/s 4-ary pulse amplitude modulation link implemented by using a 1.55 µm direct modulation laser. The results show that, compared with the traditional Volterra nonlinear equalizer, the receiver sensitivity of the equalizer is only reduced by 0.2 dB at most, but the complexity can be reduced by 50%; compared with diagonally pruned Volterra nonlinear equalizers, the complexity of the equalizer is the same, but the reception sensitivity can be improved by 0.5 dB.

Hardware-Based Architecture for DNN Wireless Communication Models.

Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing (MIMO OFDM) is a key technology for wireless communication systems. However, because of the problem of a high peak-to-average power ratio (PAPR), OFDM symbols can be distorted at the MIMO OFDM transmitter. It degrades the signal detection and channel estimation performance at the MIMO OFDM receiver. In this paper, three deep neural network (DNN) models are proposed to solve the problem of non-linear distortions introduced by the power amplifier (PA) of the transmitters and replace the conventional digital signal processing (DSP) modules at the receivers in 2 × 2 MIMO OFDM and 4 × 4 MIMO OFDM systems. Proposed model type I uses the DNN model to de-map the signals at the receiver. Proposed model type II uses the DNN model to learn and filter out the channel noises at the receiver. Proposed model type III uses the DNN model to de-map and detect the signals at the receiver. All three model types attempt to solve the non-linear problem. The robust bit error rate (BER) performances of the proposed receivers are achieved through the software and hardware implementation results. In addition, we have also implemented appropriate hardware architectures for the proposed DNN models using special techniques, such as quantization and pipeline to check the feasibility in practice, which recent studies have not done. Our hardware architectures are successfully designed and implemented on the Virtex 7 vc709 FPGA board.

Nonlinear stereophonic acoustic echo cancellation using sub-filter based adaptive algorithm

The nonlinear echo path resulting from the unwarranted acoustic echo and nonlinear distortion will degrade the echo cancellation performance of a stereophonic acoustic echo cancellation system. Techniques proposed in the literature rely on the assumption of a linear echo path. In this paper, a nonlinear stereophonic acoustic echo cancellation framework is proposed to address the problem of nonlinear distortion in stereophonic acoustic cancellation systems with a better trade-off between convergence and steady-state performance. The proposed approach uses the functional link-based adaptive filtering to deal with the nonlinear distortion in combination with the sub-filter approach to enhance the convergence performance. In addition to that, the convergence analysis of the proposed algorithm is presented in this paper. Simulations carried out using echo return loss enhancement and magnitude squared coherence as performance metrics using speech and colored noise input demonstrate the proposed framework's ability to improve the echo cancellation performance in the presence of distortion.

Improved image registration scheme based on multiscale nonlinear Harris and Gaussian–Krawtchouk moment

Image registration is an indispensable operation in image processing. To solve the problem of nonlinear distortion which easily causes low registration property, a registration scheme including a nonlinear scale space, a new discrete orthogonal Gaussian–Krawtchouk (GK) descriptor vector, and a dual similarity measurement of distance-cosine is proposed. Nonlinear scale space is constructed to preserve a lot of important structures for increasing the quantity of the salient keypoints. Meanwhile, considering both blur stability and simple computation, multiscale Harris algorithm on the basis of nonlinear scale space is applied to extract the keypoints. Moreover, according to different scales, a descriptor vector based on multiscale GK invariant moments is presented and applied to the following image matching. Finally, a dual similarity measurement of the initial Euclidean distance and the fine space cosine is proposed for the purpose of enhancing the matching accuracy. The effectiveness of the proposed algorithm has been tested on the standard images with different types of variations. The experimental results show that the performance of feature extraction and the correct matching rate of the proposed scheme are superior to those of other classical methods. The proposed scheme has a better robustness and a higher registration accuracy.

Design of Class D Audio Power Amplifier Suitable to Hearing Aid Devices

An amplifier is an electronic circuit that improves the strength of the signal. Using an amplifier in an audio system is essential to improve the strength of the signal. Based on different applications and specifications different types of amplifiers are used. Generally in an audio system, the input signal is amplified to a minimum required power level and then the speaker is driven by it. Conventionally, the output stage of an audio amplifier uses Class-A or Class-AB operating in a linear transfer region. The power efficiency of the Class-D amplifier has a better output efficiency compared to Class-A and Class-AB amplifiers, and its distortion is lower than that of the Class-C amplifier. This is based on a known fact that the Class D amplifier has a switching action in which the transistors are either completely on or off. As a result, the amplification is achieved with no power dissipation. Hence, the size of the amplifier can be highly reduced and a smaller heat sink is required. This paper focuses on designing a Class-D power amplifier which is suitable for hearing aid devices to deliver 500mW output power and for the THD to be less than 3%. The circuit implementation is done using UMC high voltage 0.18μm technology. This amplifier consists of three stages such as the modulation stage, the driver stage, the bridge stage, and the demodulation stage. Unfortunately, the Class-D power amplifier has inherent non-linear distortion problems, which is more significant than conventional audio power amplifiers. In this thesis, negative feedback is employed to reduce THD. Without feedback, the THD is obtained as above 3%. By employing feedback, the THD was reduced by 1.96dB. This design result is discussed and through to realization; whereupon the effectiveness of each of the implementation is evaluated.

Dual Gaussian attenuation model of ultrasonic echo and its parameter estimation

Signal de-noising and feature extraction, whose performance directly affect the evaluation of non-destructive testing (NDT) results, is essential technology for ultrasonic NDT echo processing. Aiming to solve the problem of nonlinear distortion between measured ultrasonic echo and its mathematical model, which widely used are exponential model (EM) and Gauss model (GM), a dual Gaussian attenuation model (DGAM) of ultrasonic echo signal and its parameter estimation method are proposed in this paper. The proposed dual Gaussian attenuation model parameter estimation (DGAM-PE) method is introduced in three parts: calculating mean square error between measured signal and model, optimizing mean square error by particle swarm optimization, optimum parameters extraction based on optimization result. The simulation and experiment results show that compared with the exponential model and Gaussian model, the proposed dual gaussian attenuation mathematical model of ultrasonic signal in this paper can better simulate the measured ultrasonic echo signal, with a mean square error of 0.0073 and normalized correlation coefficient of 0.9816. Additionally, an improved adaptive particle swarm optimization is proposed in order to enhance the accuracy of parameter estimation results.

Multiple Access With Polarity Division Sparse Code for Visible Light Communication

The increasing demand of mobile internet and Internet of Things poses challenging requirements for indoor wireless communication. Visible light communication (VLC) is a promising technology to alleviate the growing traffic problem. In addition, nonlinear distortion of light emitting diodes (LEDs) results in a poor link quality. In this paper, we propose multiple access with polarity division sparse code (PDSC) for VLC, which is based on nonorthogonal multiple access and spatial characteristic of LEDs. The experimental results indicate that the PDSC significantly enhances capacity and spectral efficiency of VLC network compared with orthogonal frequency division multiple access. We also demonstrate that the PDSC can optimize the problem of nonlinear distortion with polarity division. The experimental results reveal that PDSC is a promising multiple access scheme for the indoor VLC networks.

A Finger Vein Recognition Method Using Improved Oriented Filter and Elastic Registration

In order to reduce the influence of relative position deviation and angle deviation between minutia point sets caused by external factors when finger vein images are obtained, a finger vein recognition method using elastic registration is presented. The proposed algorithm is based on an improved neighborhood direction template and oriented filter template which facilitates the enhancement of the finger vein image while taking full account of image orientation. Elastic registration is then applied to matching of feature points within the predefined angle and radius. Applying the idea of elastic registration to existing finger vein recognition method removes the need for perfect matching between corresponding feature points and has shown to be an effective method for dealing with the problem of nonlinear distortion of images. Experimental results show that this algorithm not only overcomes the limitations of traditional point matching method, but also effectively improves the recognition performance of the system.

Frequency-domain identification algorithms for servo systems with friction

Mechanical devices usually come with undesirable nonlinearities, such as friction, backlashes, and saturations. Under the assumption of linear systems, the commonly seen identification schemes utilize sinusoidal excitation signals for parameter identification. However, the data needed for identification are unavoidably distorted by the aforementioned nonlinearities and the identification result may not be satisfactory. In the paper, binary test signals are used to perform identification, thus simplifying the behavior of friction. An identification method based on the difference of binary multifrequency excitation signals is proposed. The modified identification algorithm does not suffer from the problem of nonlinear distortions in the signal shape and is able to determine the nonlinear friction such that an accurate servo system model can be derived. A high-precision ball-screw table with asymmetric friction is identified as a test plant for this approach. The results prove that the method can be used very successfully.

On the problem of nonlinear distortions of the maximum-entropy method

We consider the problem of nonlinear distortions resulting from noise in the input data in the reconstruction of images from incomplete Fourier spectra using nonlinear information-theoretic methods, in particular, the maximum-entropy method. Comparison of traditional and generalized maximum-entropy methods shows that generalized methods, which operate in the space of complex functions, provide the best agreement of the solution with the data and, therefore, a minimal level of nonlinear distortions. Recommendations for processing of real nonnegative images of incoherent radio sources are given.

A videofluoroscopy method for optical distortion correction and measurement of knee-joint kinematics

Image distortion in video and image intensifier X-ray systems requires appropriate distortion correction methods to obtain accurate biomechanical quantitative measurements for joint kinematics applications. This paper presents an algorithm for coordinate reconstruction and distortion correction using a modified polynomial method. This algorithm was used for the measurement of patellar tendon moment arm, tibial plateau-tibial axis angle and patellar tendon-tibial axis angle during knee extension using videofluoroscopy in vivo. These parameters allow the determination of a two-dimensional biomechanical model of the knee for the measurement of muscle and joint forces during dynamic activities. Five males without knee joint injury history participated in the study. The mean measurement error obtained using an image intensifier-video system was 0.246 ± 0.111 mm over a 180-mm × 180-mm field of view. The mean maximum patellar tendon moment arm was 39.87 mm at 44.9 degrees of knee flexion. The patellar tendon-tibial plateau angle was 112.9 degrees at full extension and decreased linearly to 87.6 degrees at 90 degrees of knee flexion. The mean angle between the tibial plateau and the tibial long axis was 84.8 degrees. Applications of the method include motion analysis using video and X-ray fluoroscopy systems with non-linear distortion problems.