In this paper, Cellular Neural Networks using genetic algorithm (GA-CNNs) are designed for CMOS image noise reduction. Cellular Neural Networks (CNNs) could be an efficient way to apply to the image processing technique, since CNNs have high-speed parallel signal processing characteristics. Adaptive CNNs structure is designed for the reduction of Photon Shot Noise (PSN) changed according to the average number of photons, and the design of templates for adaptive CNNs is based on the genetic algorithm using real numbers. These templates are optimized to suppress PSN in corrupted images. The simulation results show that the adaptive GA-CNNs more efficiently reduce PSN than do the other noise reduction methods and can be used as a high-quality and low-cost noise reduction filter for PSN. The proposed method is designed for real-time implementation. Therefore, it can be used as a noise reduction filter for many commercial applications. The simulation results also show the feasibility to design the CNNs template for a variety of problems based on the statistical image model.

Image sensor noise was estimated in an approximately perceptually uniform space with a color image sensor model. Particularly, the noise level with respect to an image sensor's pixel pitch and the dark noise was investigated. It was shown that the noise level could be about half when spectral sensitivity was optimized considering noise with reduced color reproduction accuracy. It was also shown that for a 2.0 µm pixel pitch sensor, the exposure index should be less than 100-150 in order to keep the noise level 94 less than 5 even if it had no dark noise, whereas the exposure index could reach about 2000-4000 for a 8.0 µm pixel pitch sensor depending on the sensor sensitivity and the dark noise level.

We have developed a new simulation methodology for predicting shot noise intensity in Metal-Oxide-Semiconductor Field Effect Transistor (MOSFET). In our approach, shot noise in MOSFETs is calculated by employing a two dimensional device simulator in conjunction with the shot noise model of a p-n junction. The accuracy of the noise model has been demonstrated by comparing simulation results with measured noise data of p-n diodes. The intensity of shot noise in various n-MOSFET devices under various bias conditions was estimated beyond GHz operational frequency by using our simulation scheme. At DC or low-frequency region, sub-threshold current dominates the intensity of shot noise. Therefore, shot noise is independent on frequency in this region, and its intensity is exponentially depends on VG, proportional to L-1, and almost independent on VD. At high-frequency region above GHz frequency, on the other hand, shot noise intensity depends on frequency and is much larger than that of low-frequency region. In particular, the intensity of the RF shot noise is almost independent on L, VD and VG. This suggests that high-frequency shot noise intensity of MOSFETs is decided only by the conditions of source-bulk junction.

This paper concentrates on the model useful for analyzing the error performance of M-estimators of a single unknown signal parameter: that is the error intensity model. We develop the point process representation for the estimation error, the conditional distribution of the estimator, and the distribution of error candidate point process. Then the error intensity function is defined as the probability density of the estimate and the general form of the error intensity function is derived. We compute the explicit form of the intensity functions based on the local maxima model of the error generating point process. While the methods described in this paper are applicable to any estimation problem with continuous parameters, our main application will be time delay estimation. Specifically, we will consider the case where coherent impulsive interference is involved in addition to the Gaussian noise. Based on numerical simulation results, we compare each of the error intensity model in terms of the accuracy of both error probability and mean squared error (MSE) predictions, and the issue of extendibility to multiple parameter estimation is also discussed.

We investigate the intrinsic current fluctuations in small Si-MOSFETs via the Monte Carlo device simulation. It is demonstrated that the temporal fluctuation of the drain current in Si-MOSFETs attains a significant fraction of the averaged drain current when the device width is scaled down to the deep sub-µm regime. This is caused by the drastic decrease in the number of channel electrons. This finding holds true whenever the device width is reduced to deep sub-µm, regardless of the channel length. Most importantly, current fluctuation is associated with the quasi-equilibrium thermal noise in the heavily-doped source and drain regions, whereas its magnitude with respect to the averaged drain current is directly related to the number of channel electrons underneath the gate.

While Electro-Optic (E-O) sampling has achived the electric signal measurement with advantages of noninvasive, noncontact and ultrafast time resolution, it is unsuitable for measuring long logic patterns in fast ICs under the functional test conditions. To overcome this problem, a real time E-O probing using a continuous wave (CW) diode laser and a fast photodetector has been developed. By adopting a ZnTe E-O probe having a half-wave voltage of 3.6 kV, shot noise limited measurement with a frequency bandwidth of 480 MHz has been achieved using a low noise diode laser (wavelength of 780 nm, output power of 30 mW), a pin photodiode, a wideband low noise amplifier, and a digital oscilloscope having 500 MHz bandwidth as a waveform analyzer. The minimum detectable voltage was 23 mV under 700 times integration. In this paper, discussion of the voltage sensitivity of real time E-O probing is included. Key parameters for attaining the highly sensitive real time E-O probing are the sensitivity of the E-O probe and noises of the probing light and detection system.

In this paper, we analyze a photodetection process of new kind theoretically, which transforms a coherent state of light so as to lead to nonstandard property, namely, sub-Poissonian distribution of its output photoelectron during its photodetection process. The properties of the photoelectron distribution are studied used as preamplifiers of both direct-detection and homodyne detection cases.