• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.6
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• pp.619-628
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• 2019

In this paper, we designed a beta ray sensor for a true random number generator. Instead of biasing the gate of the PMOS feedback transistor to a DC voltage, the current flowing through the PMOS feedback transistor is mirrored through a current bias circuit designed to be insensitive to PVT fluctuations, thereby minimizing fluctuations in the signal voltage of the CSA. In addition, by using the constant current supplied by the BGR (Bandgap Reference) circuit, the signal voltage is charged to the VCOM voltage level, thereby reducing the change in charge time to enable high-speed sensing. The beta ray sensor designed with 0.18㎛ CMOS process shows that the minimum signal voltage and maximum signal voltage of the CSA circuit which are resulted from corner simulation are 205mV and 303mV, respectively. and the minimum and maximum widths of the pulses generated by comparing the output signal through the pulse shaper with the threshold voltage (VTHR) voltage of the comparator, were 0.592㎲ and 1.247㎲, respectively. resulting in high-speed detection of 100kHz. Thus, it is designed to count up to 100 kilo pulses per second.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.295-298
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• 2014

In this paper, an efficient design of HEVC Adaptive Loop Filter(ALF) for filter coefficients estimation is proposed. The ALF performs Cholesky decomposition of $10{\times}10$ matrix iteratively to estimate filter coefficients. The Cholesky decomposition of the ALF consists of root and division operation which is difficult to implement in a hardware design because it needs to many computation rate and processing time due to floating-point unit operation of large values of the Maximum 30bit in a LCU($64{\times}64$). The proposed hardware architecture is implemented by designing a root operation based on Cholesky decomposition by using multiplexer, subtracter and comparator. In addition, The proposed hardware architecture of efficient and low computation rate is implemented by designing a pipeline architecture using characteristic operation steps of Cholesky decomposition. An implemented hardware is designed using Xilinx ISE 14.3 Vertex-6 XC6VCX240T FPGA device and can support a frame rate of 40 4K Ultra HD($4096{\times}2160$) frames per second at maximum operation frequency 150MHz.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.9
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• pp.63-73
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• 2015

This work proposes a 2-channel time-interleaved (T-I) 10b 120MS/s pipeline SAR ADC minimizing offset mismatch between channels without any calibration scheme. The proposed ADC employs a 2-channel SAR and T-I topology based on a 2-step pipeline ADC with 4b and 7b in the first and second stage for high conversion rate and low power consumption. Analog circuits such as comparator and residue amplifier are shared between channels to minimize power consumption, chip area, and offset mismatch which limits the ADC linearity in the conventional T-I architecture, without any calibration scheme. The TSPC D flip-flop with a short propagation delay and a small number of transistors is used in the SAR logic instead of the conventional static D flip-flop to achieve high-speed SAR operation as well as low power consumption and chip area. Three separate reference voltage drivers for 4b SAR, 7b SAR circuits and a single residue amplifier prevent undesirable disturbance among the reference voltages due to each different switching operation and minimize gain mismatch between channels. High-frequency clocks with a controllable duty cycle are generated on chip to eliminate the need of external complicated high-frequency clocks for SAR operation. The prototype ADC in a 45nm CMOS technology demonstrates a measured DNL and INL within 0.69LSB and 0.77LSB, with a maximum SNDR and SFDR of 50.9dB and 59.7dB at 120MS/s, respectively. The proposed ADC occupies an active die area of 0.36mm2 and consumes 8.8mW at a 1.1V supply voltage.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1041-1043
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• 1993

Fuzzy logic based Control Theory has gained much interest in the industrial world, thanks to its ability to formalize and solve in a very natural way many problems that are very difficult to quantify at an analytical level. This paper shows a solution for treating membership function inside hardware circuits. The proposed hardware structure optimizes the memoried size by using particular form of the vectorial representation. The process of memorizing fuzzy sets, i.e. their membership function, has always been one of the more problematic issues for the hardware implementation, due to the quite large memory space that is needed. To simplify such an implementation, it is commonly [1,2,8,9,10,11] used to limit the membership functions either to those having triangular or trapezoidal shape, or pre-definite shape. These kinds of functions are able to cover a large spectrum of applications with a limited usage of memory, since they can be memorized by specifying very few parameters ( ight, base, critical points, etc.). This however results in a loss of computational power due to computation on the medium points. A solution to this problem is obtained by discretizing the universe of discourse U, i.e. by fixing a finite number of points and memorizing the value of the membership functions on such points [3,10,14,15]. Such a solution provides a satisfying computational speed, a very high precision of definitions and gives the users the opportunity to choose membership functions of any shape. However, a significant memory waste can as well be registered. It is indeed possible that for each of the given fuzzy sets many elements of the universe of discourse have a membership value equal to zero. It has also been noticed that almost in all cases common points among fuzzy sets, i.e. points with non null membership values are very few. More specifically, in many applications, for each element u of U, there exists at most three fuzzy sets for which the membership value is ot null [3,5,6,7,12,13]. Our proposal is based on such hypotheses. Moreover, we use a technique that even though it does not restrict the shapes of membership functions, it reduces strongly the computational time for the membership values and optimizes the function memorization. In figure 1 it is represented a term set whose characteristics are common for fuzzy controllers and to which we will refer in the following. The above term set has a universe of discourse with 128 elements (so to have a good resolution), 8 fuzzy sets that describe the term set, 32 levels of discretization for the membership values. Clearly, the number of bits necessary for the given specifications are 5 for 32 truth levels, 3 for 8 membership functions and 7 for 128 levels of resolution. The memory depth is given by the dimension of the universe of the discourse (128 in our case) and it will be represented by the memory rows. The length of a world of memory is defined by: Length = nem (dm(m)＋dm(fm) Where: fm is the maximum number of non null values in every element of the universe of the discourse, dm(m) is the dimension of the values of the membership function m, dm(fm) is the dimension of the word to represent the index of the highest membership function. In our case then Length=24. The memory dimension is therefore 128*24 bits. If we had chosen to memorize all values of the membership functions we would have needed to memorize on each memory row the membership value of each element. Fuzzy sets word dimension is 8*5 bits. Therefore, the dimension of the memory would have been 128*40 bits. Coherently with our hypothesis, in fig. 1 each element of universe of the discourse has a non null membership value on at most three fuzzy sets. Focusing on the elements 32,64,96 of the universe of discourse, they will be memorized as follows: The computation of the rule weights is done by comparing those bits that represent the index of the membership function, with the word of the program memor . The output bus of the Program Memory (μCOD), is given as input a comparator (Combinatory Net). If the index is equal to the bus value then one of the non null weight derives from the rule and it is produced as output, otherwise the output is zero (fig. 2). It is clear, that the memory dimension of the antecedent is in this way reduced since only non null values are memorized. Moreover, the time performance of the system is equivalent to the performance of a system using vectorial memorization of all weights. The dimensioning of the word is influenced by some parameters of the input variable. The most important parameter is the maximum number membership functions (nfm) having a non null value in each element of the universe of discourse. From our study in the field of fuzzy system, we see that typically nfm 3 and there are at most 16 membership function. At any rate, such a value can be increased up to the physical dimensional limit of the antecedent memory. A less important role n the optimization process of the word dimension is played by the number of membership functions defined for each linguistic term. The table below shows the request word dimension as a function of such parameters and compares our proposed method with the method of vectorial memorization[10]. Summing up, the characteristics of our method are: Users are not restricted to membership functions with specific shapes. The number of the fuzzy sets and the resolution of the vertical axis have a very small influence in increasing memory space. Weight computations are done by combinatorial network and therefore the time performance of the system is equivalent to the one of the vectorial method. The number of non null membership values on any element of the universe of discourse is limited. Such a constraint is usually non very restrictive since many controllers obtain a good precision with only three non null weights. The method here briefly described has been adopted by our group in the design of an optimized version of the coprocessor described in [10].

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.48 no.5
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• pp.25-33
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• 2011

This work proposes a skinny-type 10b 50MS/s 0.13um CMOS three-step pipeline ADC for CIS applications. Analog circuits for CIS applications commonly employ a high supply voltage to acquire a sufficiently acceptable dynamic range, while digital circuits use a low supply voltage to minimize power consumption. The proposed ADC converts analog signals in a wide-swing range to low voltage-based digital data using both of the two supply voltages. An op-amp sharing technique employed in residue amplifiers properly controls currents depending on the amplification mode of each pipeline stage, optimizes the performance of op-amps, and improves the power efficiency. In three FLASH ADCs, the number of input stages are reduced in half by the interpolation technique while each comparator consists of only a latch with low kick-back noise based on pull-down switches to separate the input nodes and output nodes. Reference circuits achieve a required settling time only with on-chip low-power drivers and digital correction logic has two kinds of level shifter depending on signal-voltage levels to be processed. The prototype ADC in a 0.13um CMOS to support 0.35um thick-gate-oxide transistors demonstrates the measured DNL and INL within 0.42LSB and 1.19LSB, respectively. The ADC shows a maximum SNDR of 55.4dB and a maximum SFDR of 68.7dB at 50MS/s, respectively. The ADC with an active die area of 0.53$mm^2$ consumes 15.6mW at 50MS/s with an analog voltage of 2.0V and two digital voltages of 2.8V ($=D_H$) and 1.2V ($=D_L$).