Realization of Delayed Least Mean Square Adaptive Algorithm using Verilog HDL for EEG Signals

An efficient architecture for the implementation of delayed least mean square (DLMS) adaptive filter is presented in this paper. It is shown that the proposed architectures reduces the register complexity and also supports the faster convergence. Compared to transpose form, the direct form LMS adaptive filter has fast convergence but both has most similar critical path. Further it is shown that in most of the practical cases, very small adaptation delay is sufficient enough to implement a direct-form LMS adaptive filter where in normal cases a very high sampling rate is required and also it shows that no pipelining approach is necessary. From the above discussed estimations three different architectures of LMS adaptive filter has been designed. They are, first design comprise of zero delays i.e., with no adaptation delays, second design comprises of only single delay i.e., with only one adaptation delay, and lastly the third design comprises of two adaptation delays. Among all the three designs zero adaptation delay structure gives efficient performance comparatively. Design with zero adaptation delay involves the minimum energy per sample (EPS) and also minimum area compared to other two designs. The aim of this thesis is to design an efficient filter structures to create a system-on-chip (SoC) solution by using an optimized code for solving various adaptive filtering problems in the system. In this thesis our main focus is on interference cancellation in electroencephalogram (EEG) applications by using the proposed filter structures. Modern field programmable gate arrays (FPGAs) have the resources that are required to design an effective adaptive filtering structures. The designs are evaluated in terms of design time, area and delays

Memristor-Based Digital Systems Design and Architectures

Memristor is considered as a suitable alternative solution to resolve the scaling limitation of CMOS technology. In recent years, the use of memristors in circuits design has rapidly increased and attracted researcher’s interest. Advances have been made to both size and complexity of memristor designs. The development of CMOS transistors shows major concerns, such as, increased leakage power, reduced reliability, and high fabrication cost. These factors have affected chip manufacturing process and functionality severely. Therefore, the demand for new devices is increasing. Memristor, is considered as one of the key element in memory and information processing design due to its small size, long-term data storage, low power, and CMOS compatibility. The main objective in this research is to design memristor-based arithmetic circuits and to overcome some of the Memristor based logic design issues. In this thesis, a fast, low area and low power hybrid CMOS memristor based digital circuit design were implemented. Small and large-scale memristor based digital circuits are implemented and provided a solutions for overcoming the memristor degradation and fan-out challenges. As an example, a 4- bit LFSR has been implemented by using MRL scheme with 64 CMOS devices and 64 memristors. The proposed design is more efficient in terms of the area when compared with CMOS- based LFSR circuits. The simulation results proves the functionality of the design. This approach presents acceptable speed in comparison with CMOS-based design and it is faster than IMPLY-based memrisitive LFSR. The propped LFSR has 841 ps de-lay. Furthermore, the proposed design has a significant power reduction of over 66% less than CMOS-based approach. This thesis proposes implementation of memristive 2-D median filter and extends previously published works on memristive Filter design to include this emerging technology characteristics in image processing. The proposed circuit was designed based on Pt/TaOx/Ta redox-based device and Memristor Ratioed Logic (MRL). The proposed filter is designed in Cadence and the memristive median approved tested circuit is translated to Verilog-XL as a behavioral model. Different 512 _ 512 pixels input images contain salt and pepper noise with various noise density ratios are applied to the proposed median filter and the design successfully has substantially removed the noise. The implementation results in comparison with the conventional filters, it gives better Peak Signal to Noise Ratio (PSNR) and Mean Absolute Error (MAE) for different images with different noise density ratios while it saves more area as compared to CMOS-based design. This dissertation proposes a comprehensive framework for design, mapping and synthesis of large-scale memristor-CMOS circuits. This framework provides a synthesis approach that can be applied to all memristor-based digital logic designs. In particular, it is a proposal for a characterization methodology of memristor-based logic cells to generate a standard cell library for large scale simulation. The proposed framework is implemented in the Cadence Virtuoso schematic-level environment and was veri_ed with Verilog-XL, MATLAB, and the Electronic Design Automation (EDA) Synopses compiler after being translated to the behavioral level. The proposed method can be applied to implement any digital logic design. The frame work is deployed for design of the memristor-based parallel 8-bit adder/subtractor and a 2-D memristive-based median filter

MODELING AND CONTROL OF DIRECT-CONVERSION HYBRID SWITCHED-CAPACITOR DC-DC CONVERTERS

Efficient power delivery is increasingly important in modern computing, communications, consumer and other electronic systems, due to the high power demand and thermal concerns accompanied by performance advancements and tight packaging. In pursuit of high efficiency, small physical volume, and flexible regulation, hybrid switched-capacitor topologies have emerged as promising candidates for such applications. By incorporating both capacitors and inductors as energy storage elements, hybrid topologies achieve high power density while still maintaining soft charging and efficient regulation characteristics. However, challenges exist in the hybrid approach. In terms of reliability, each flying capacitor should be maintained at a nominal `balanced\u27 voltage for robust operation (especially during transients and startup), complicating the control system design. In terms of implementation, switching devices in hybrid converters often need complex gate driving circuits which add cost, area, and power consumption. This dissertation explores techniques that help to mitigate the aforementioned challenges. A discrete-time state space model is derived by treating the hybrid converter as two subsystems, the switched-capacitor stage and the output filter stage. This model is then used to design an estimator that extracts all flying capacitor voltages from the measurement of a single node. The controllability and observability of the switched-capacitor stage reveal the fundamental cause of imbalance at certain conversion ratios. A new switching sequence, the modified phase-shifted pulse width modulation, is developed to enable natural balance in originally imbalanced scenarios. Based on the model, a novel control algorithm, constant switch stress control, is proposed to achieve both output voltage regulation and active balance with fast dynamics. Finally, the design technique and test result of an integrated hybrid switched-capacitor converter are reported. A proposed gate driving strategy eliminates the need for external driving supplies and reduces the bootstrap capacitor area. On-chip mixed signal control ensures fast balancing dynamics and makes hard startup tolerable. This prototype achieves 96.9\% peak efficiency at 5V:1.2V conversion and a startup time of 12$\mu s$, which is over 100 times faster than the closest prior art. With the modeling, control, and design techniques introduced in this dissertation, the application of hybrid switched-capacitor converters may be extended to scenarios that were previously challenging for them, allowing enhanced performance compared to using traditional topologies. For problems that may require future attention, this dissertation also points to possible directions for further improvements