This paper reviews production testing issues for analog and mixed-signal SoC in IoT era for analog circuit designers, and also introduces research examples including authors' group research results in this area. Notice that production testing and measurement/characterization for ICs are similar but different, and this paper introduces the former. For IoT systems and automotive applications, analog and mixed-signal circuit testing is very important to realize their reliability at low cost, and there are a lot of technology challenges. Their overview including future technology challenges is described.

Low noise amplifiers (LNAs) are a crucial component of RF circuits such as receivers. The noise figure (NF) determines on LNA performance. There are several different noise cancellation techniques. For example, to reduce noise, a feedforward-type noise removal method is effective. In this paper, we propose a new feed-forward noise cancellation method considering two different signal paths and compare it with the conventional NF based method. Specter simulations were performed using a 0.18µm 1-poly 5-metal CMOS BSIM model.

In this paper, we propose the expanding technique of the ΔΣ ADC dynamic range by changing a feedback coefficient. The feedback coefficient is switched from 1 to 0.5 according to the input signal voltage value. It can improve the SNR at the small amplitude input reducing the quantization noise by the small feedback coefficient. We confirmed by the circuit simulation that the proposed circuit archives a dynamic range of 102 dB, and improves SNR of 6 dB from the conventional circuit.

The frequency error and the phase noise decide on the performance of PLL. The phase noise of PLL is proportional to jitter. The jitter is degraded due to the dead time of the phase detector. In this paper, we proposed the time amplifier (TimeAMP) phase detector for reducing the dead time of the phase detector. The control pulse width of the charge pump switches is amplified from the time lag of input pulses by TimeAMP. We confirm by the transistor level simulation that the dead time is reduced to 1/100 and the lock time is reduced to 1/2.

The grid connection inverter is built in the PCS (Power Conditioning Subsystem) for the distributed power supply, such as photovoltaic system. Recently, the researches on power flow using PCS have been advanced. In order to adjust the power of PCS, it is necessary that the grid connection inverter of the PCS predicts the load and output fluctuation in customer side. Therefore, this paper investigates a load estimation in the grid connection inverter of the PCS under load shift. The proposed estimation method adds superimposing pseudo white signal in the inverter reference signal. In addition, the pseudo random binary sequence (PRBS) creates the pseudo white signal for load estimation. As a result, the proposed method achieves the load estimation even under load shift.

Previously, the method has been proposed to reduce the quantization noise of the fractional N-PLL and the spurious due to the reference leak by placing a DLL before the PLL. We have previously proposed Multiplied ΔΣTDC, which solves the phase noise problem and spurious due to DLL delay device manufacturing variation. However, in the previous proposal, there was a trade-off between spurious reduction and quantization noise improvement by ΔΣTDC. In this paper, we propose a Multiplied ΔΣTDC that solves this problem and always has the effect of Noise shaping by ΔΣTDC.

This paper proposes a design methodology of LC-simulation type filters using operational transconductance amplifiers in order to minimize filter output noise. Comparison between the proposed method and a conventional one is shown. Simulation results demonstrate validity of the proposed method.

A large current generating apparatus is used for a power system testing apparatus or a power supply apparatus for a magnetic inspection apparatus, and supplies a large current output to a low resistance load. The transformer used for large current output is driven at commercial frequency and the challenge is to improve power efficiency.

In this paper, by changing the wave-form of driving voltage for the transformer used in the high power output equipment to the ternary pulse of the same frequency from the conventional sine wave, it was shown that the iron loss of transformer could be reduced applying by 14% while maintaining the effective value of the output current. In addition, it was also shown that by the unipolar PWM driving for the transformer, the iron loss could be reduced to 89% of that in bipolar PWM system with the miniaturization of the transformer size.

A non mechanical scanning method is developed for mapping absolute vibrational patterns of a polishing surface piezoelectric device. In this paper, by improving the traditional Laser Speckle method, we first proved the method can measure the polished scattered light of the smooth surfaces. As a result, using 377nm of an ultraviolet laser device, the simulation of the polished surface was carried out to 45 from 10 degrees, and, moreover, the reflection coefficients found area of 35% or less by the measurements.

Under ideal conditions with low noise, the acoustic distance measurement (ADM) method using the cross-spectrum for adjacent 2ch observations shows sufficient distance estimation performance. Increasing noise will deteriorate the distance estimation performance. To reduce noise, even if complex ICA is applied to adjacent 2ch noisy observations, sufficient separation performance for distance measurement cannot be exhibited, because the microphones are too close. Thus, if the ADM method using the cross-spectrum is applied to the separated signals of the adjacent 2ch noisy observations, an incorrect distance near 0 m is estimated because of the effect of measurement system. Therefore, by increasing the number of microphones (which increases information and can be expected to improve the separation performance), and applying complex ICA to improve the separation performance, ADM using the cross-spectrum for the new separation signals is proposed. This method enables us to obtain distance estimation that eliminates both environmental noise and the effect of the measurement system. The validity of the proposed method is also verified with the experiment of the actual distance measurement. As a result, it was found that the distance 1 m to the target can be measured under the noise of SNR (Signal to Noise Ratio) -10 dB.

Since the world faces to the realization of “the low-carbon world”, renewable energies have been attracting attention. Due to the estimated ocean-wave power capacity is large, wave power generations are one of the promising renewable energy. However, the system using the rotational motor and the conventional linear motor has problems caused by the mechanical loss and the output power amount. On the other hand, the authors have proposed “a helical motor” as a high thrust-density linear motor and the damping control using this motor. In the latest study, deriving the optimal damping gain, the regenerative efficiency maximization control for the motor was proposed and basically validated. In this paper, firstly, in comparison with the experiment, the numerical simulation, and the derived theoretical response, the calculations were validated. Then, from the numerical and theoretical analysis, the proposed control and design method were discussed. From this discussion, it can conclude the proposed design method can predict the existence range of the optimal damper gain.

Predicting the human visual attention in an image is called saliency prediction, and is an active research area in the field of neuroscience and computer vision. Early works on saliency prediction was performed by using low-level features. In recent years, convolutional neural networks (CNN) have been adapted for saliency prediction and achieved the state-of-the-art performance. However, the eye-gaze depends on the personality of each viewer⁽¹⁾ and conventional methods did not take into account such individual properties of the viewer. Therefore, this paper proposes a novel saliency prediction method considering the influence of eye-gaze. Assuming that personality can be expressed as the degree of attention to an object, our proposed method considers the personality by learning which objects are likely to be perceived by each viewer, and weighting the universal saliency map with the generated mask based on the object detection results. The experimental results show that the proposed universal saliency map achieves higher accuracy than conventional methods on the public dataset, and the proposed weighted saliency map can reflect the variation of the eye-gaze influences among viewers.