With the gradually increase of the application of new energy in microgrids, Electric Spring (ES), as a new type of distributed compensation power electronic device has been widely studied. The Generalized Electric Spring (G-ES) is an improved topology, and the space limitation problem in the traditional topology is solved. Because of the mode of G-ES use in the power grid, a reasonable solution to the voltage loss of the critical section feeder is needed. In this paper, the voltage balance equation based on the feedforward compensation coefficient is established, and a two cascade control strategy based on the equation is studied. The first stage of the two cascade control strategy is to use communication means to realize the allocation of feedforward compensation coefficients, and the second stage is to use the coefficients to realize feedforward fixed angle control. Simulation analysis shows that the proposed control strategy does not affect the control accuracy of the critical load (CL), and effectively improves the operational range of the G-ES.

In this letter, we consider a global stabilization problem for a class of feedforward systems by an event-triggered control. This is an extended work of [10] in a way that there are uncertain feedforward nonlinearity and time-varying input delay in the system. First, we show that the considered system is globally asymptotically stabilized by a proposed event-triggered controller with a gain-scaling factor. Then, we also show that the interexecution times can be enlarged by adjusting a gain-scaling factor. A simulation example is given for illustration.

We propose a deep learning-based model for classifying pathological voices using a convolutional neural network and a feedforward neural network. The model uses combinations of heterogeneous parameters, including mel-frequency cepstral coefficients, linear predictive cepstral coefficients and higher-order statistics. We validate the accuracy of this model using the Massachusetts Eye and Ear Infirmary (MEEI) voice disorder database and the Saarbruecken Voice Database (SVD). Our model achieved an accuracy of 99.3% for MEEI and 75.18% for SVD. This model achieved an accuracy that is 7.18% higher than that of competitive models in previous studies.

In this letter, we investigate the problem of feedforward timing estimation for burst-mode satellite communications. By analyzing the correlation property of frame header (FH) acquisition in the presence of sampling offset, a novel data-aided feedforward timing estimator that utilizes the correlation peaks for interpolating the fractional timing offset is proposed. Numerical results show that even under low signal-to-noise ratio (SNR) and small rolloff factor conditions, the proposed estimator can approach the modified Cramer-Rao bound (MCRB) closely. Furthermore, this estimator only requires two samples per symbol and can be implemented with low complexity with respect to conventional data-aided estimators.

This paper proposes 1-bit feedforward distortion compensation for digital radio frequency conversion (DRFC) with 1-bit bandpass delta-sigma modulation (BP-DSM). The 1-bit BP-DSM allows direct RF signal transmission from a digitally modulated signal. However, it has been previously reported that 1-bit digital pulse trains with non-ideal rectangle waveform cause spectrum regrowth. The proposed architecture adds a feedforward path with another 1-bit BP-DSM and so can cancel out the distortion components at any target carrier frequency. Both the main signal and the distortion compensation signal are 1-bit digital pulse trains and so no additional analog RF circuit is required for distortion compensation. Simulation results show that the proposed method holds the adjacent channel leakage ratio to 60dB for LTE signal transmission. A prototype of the proposed 1-bit DRFC with an additional 1-bit BP-DSM in the feedforward path shows an ACLR of 50dB, 4dB higher than that of the conventional 1-bit DRFC.

This paper proposes the state observer design for feedforward nonlinear systems with delayed output. It is shown that by using the Lyapunov-Krasovskii functional, the proposed design method ensures the asymptotic stability of estimation error for an arbitrarily large output delay. Finally, an illustrative example is given in order to show the effectiveness of our design method.

It is shown that simple preprocessing on the reference signals in multichannel feedforward ANC system can improve the convergence performance of the adaptive ANC algorithm. A fast and efficient blind preprocessing algorithm in frequency domain is proposed to reduce the computational complexity even that the reference sensors are located far from the noise sources. The permutation problem at different frequency bin is also addressed and solved by an independent vector analysis algorithm. The basic principle and performance comparison are given to verify our conclusion.

This letter proposes a method for choosing the best quantized beamforming vector that represents a subcarrier group, for coordinated beamforming in the downlink of multiuser multiple input multiple output-orthogonal frequency division multiplexing systems. The correlation between subcarriers is exploited for reducing the feedforward overhead, while maximizing the sum rate.

We consider a stabilization problem of a class of input-delayed nonlinear systems that have not only feedforward, but also some non-feedforward nonlinearity. While there are some existing results that deal with input-delayed non-feedforward nonlinear systems, they often assume a small input delay. It has been often the case that for a large input delay, the results are limited to only feedforward systems. In this letter, combined with the LMI approach in [3] and the reduction method in [5], we show that some feedforward and non-feedforward systems with a large delay in the input can be stabilized via the proposed controller.

We present the recovery of 2.5 Gb/s synchronous 16-point quadrature amplitude modulation data in real-time for an linewidth-times-symbol-duration ratio of 0.00048 after transmission over 1.6 km standard single mode fiber.

This paper describes the design methodology of a low dropout regulator (LDO). It was used to develop a power management sub-system IC for CDMA handsets which is also described in this paper. This IC contains 11 LDOs, bandgap reference, battery charger, control logic and some other peripheral circuits. For CDMA applications, very small ground current in the order of µA in standby mode is required for LDOs. An LDO architecture to meet this requirement and achieve stable operation over the process variation was developed. The on-chip logic efficiently controls all LDOs and battery charger to reduce the power dissipation as much as possible. This mixed signal subsystem has been implemented in the in-house 0.6-µm BCDMOS process. The very low LDO ground current down to 3 µA has been achieved with stable operation.

A linear model for feedforward ring oscillators (FROs) is developed and oscillator characteristics are analyzed using the model. The model allows prediction of multiple oscillation modes as well as the oscillation frequency of each mode. The prediction agrees well with SPICE simulation results.

Based on the theoretical analysis of literature, saturation in measured signal of active noise control (ANC) systems will degrade the convergence speed. However, the experiments show that the saturated input signal can speed up the convergence of the narrow-band ANC systems. This paper intends to remodel the saturation effects for feedforward and feedback ANC systems. Combining the action of analog-to-digital converters (ADC), the mathematical expression and block diagrams are proposed to model the saturation effects in the practical ANC systems. The derivation and simulation results show that since the saturation is able to amplify the principle component of signal, the convergence would be speeded up.

We propose a novel 50 Mb/s optical transmitter fabricated in a 0.6 µm BiCMOS technology for automotive applications. The proposed VCSEL driver chip was designed to operate with a single supply voltage ranging from 3.0 V to 5.25 V. A fully integrated feedforward current control circuit is presented to stabilize the optical output power without any external components. The experimental results show that the optical output power can be stable within a 1.1 dB range and the extinction ratio greater than 14 dB over the automotive environmental temperature range of -40 to 105.

Complex bandpass ΔΣAD modulators can provide superior performance to a pair of real bandpass ΔΣAD modulators of the same order. They process just input I and Q signals, not image signals, and AD conversion can be realized with low power dissipation, so that they are desirable for such low-IF receiver applications. This paper proposes a new architecture for complex bandpass Δ ΣAD modulators with cross-noise-coupled topology, which effectively raises the order of the complex modulator and achieves higher SQNDR (Signal to Quantization Noise and Distortion Ratio) with low power dissipation. By providing the cross-coupled quantization noise injection to internal I and Q paths, noise coupling between two quantizers can be realized in complex form, which enhances the order of noise shaping in complex domain, and provides a higher-order NTF using a lower-order loop filter in the complex ΔΣAD modulator. Proposed higher-order modulator can be realized just by adding some passive capacitors and switches, the additional integrator circuit composed of an operational amplifier is not necessary, and the performance of the complex modulator can be effectively raised without more power dissipation. We have performed simulation with MATLAB to verify the effectiveness of the proposed architecture. The simulation results show that the proposed architecture can achieve the realization of higher-order enhancement, and improve SQNDR of the complex bandpass ΔΣAD modulator.

The single-hidden-layer feedforward neural networks (SLFNs) are frequently used in machine learning due to their ability which can form boundaries with arbitrary shapes if the activation function of hidden units is chosen properly. Most learning algorithms for the neural networks based on gradient descent are still slow because of the many learning steps. Recently, a learning algorithm called extreme learning machine (ELM) has been proposed for training SLFNs to overcome this problem. It randomly chooses the input weights and hidden-layer biases, and analytically determines the output weights by the matrix inverse operation. This algorithm can achieve good generalization performance with high learning speed in many applications. However, this algorithm often requires a large number of hidden units and takes long time for classification of new observations. In this paper, a new approach for training SLFNs called least-squares extreme learning machine (LS-ELM) is proposed. Unlike the gradient descent-based algorithms and the ELM, our approach analytically determines the input weights, hidden-layer biases and output weights based on linear models. For training with a large number of input patterns, an online training scheme with sub-blocks of the training set is also introduced. Experimental results for real applications show that our proposed algorithm offers high classification accuracy with a smaller number of hidden units and extremely high speed in both learning and testing.

This paper proposes novel feedforward architecture of the second-order multibit ΔΣAD modulator with single DAC-feedback topology. The ΔΣAD modulator realizes high resolution by oversampling and noise shaping techniques. However, its SNDR (Signal to Noise and Distortion Ratio) is limited by the dynamic range of the input signal and non-idealities of circuit building blocks, particularly by the harmonic distortion in amplifier circuits. A full feedforward ΔΣAD modulator structure has the signal transfer function of unity under ideal circumstances, which means that the signal swings through the loop filter become smaller compared with a feedbacked ΔΣAD modulator. Therefore, the harmonic distortion generated inside the loop filter can be significantly reduced in the feedforward structure because the effect of non-idealities in amplifiers can be suppressed when signal swing is small. Moreover, the reduction of the internal signal swings also relaxes output swing requirements for amplifiers with low supply voltage. However, in conventional feedforward ΔΣAD modulator, an analog adder is needed before quantizer, and especially in a multibit modulator, an additional amplifier is necessary to realize the summation of feedforward signals, which leads to extra chip area and power dissipation. In this paper, we propose a novel architecture of a feedforward ΔΣAD modulator which realizes the summation of feedforward signals without additional amplifier. The proposed architecture is functionally equivalent to the conventional one but with smaller chip area and lower power dissipation. We conducted MATLAB and SPICE simulations to validate the proposed architecture and modulator circuits.

This paper describes 10-bit, 80-MSample/s pipelined A/D converters for wireless-communication terminals. To reduce power consumption, we employed the I/Q amplifier sharing technique [1] in which an amplifier is used for both I and Q channels. In addition, common-source, pseudo-differential (PD) amplifiers are used in all the conversion stages for further power reduction. Common-mode disturbances are removed by the proposed common-mode feedforward (CMFF) technique without using fully differential (FD) amplifiers. The converter was implemented in a 90-nm CMOS technology, and it consumes only 24 mW/ch from a 1.2-V power supply. The measured SNR and SNDR are 58.6 dB and 52.2 dB, respectively.

A compact OTA suitable for low-voltage active-RC and MOSFET-C filters is presented. The input stage of the OTA utilises the NMOS pseudo-differential amplifier with PMOS active load. The output stage relies upon the dual-mode feed-forward class-AB technique (based on an inverter-type transconductor) with common-mode rejection capability that incurs no penalty on transconductance/bias-current efficiency. Simulation results of a 0.5-V 100-kHz 5th-order Chebyshev filter based on the proposed OTA in a 0.18 µm CMOS process indicate SNR and SFDR of 68 dB and 63 dB (at 50 kHz+55 kHz) respectively. The filter consumes total power consumption of 60 µW.

In this letter, we consider a class of approximately feedback linearized systems that contain both triangular and feedforward forms. With a utilization of the transformation scaling factor, we analytically show that the considered system can be globally exponentially stabilized, globally bounded, or locally stabilized depending on the shapes of triangular and feedforward forms. Our new method broadens a class of nonlinear systems under consideration over the existing results.