Proposed Analog Circuit Research Articles

From coexisting attractors to multi-spiral chaos in a ring of three coupled excitation-free Duffing oscillators

The dynamics of a ring of three unidirectional coupled excitation-free double well Duffing oscillators is considered. The coupling technique followed in this work consists in the amplitude modulation of an oscillator with a proportion of the amplitude of its neighboring counterpart. The rate equation of this model is a sixth-order autonomous nonlinear odd symmetric system endowed with twenty seven equilibrium points eight of which undergo Hopf bifurcation. A detailed analysis of the model based on classic nonlinear analysis tools (e.g. bifurcation diagrams, phase portraits, basins of attraction) discloses attractive and interesting dynamical features such as eight parallel bifurcation threes, Hopf bifurcations, and various types of coexisting modes of oscillations (e.g. eight coexisting limit cycles, four competing double spiral chaotic attractors, two coexisting four-spiral chaotic attractors), and eight-spiral chaotic attractor, just to cite a few. The electronic circuit implementation of the three coupled Duffing oscillators system was executed based on simple available electronic components. The simulation study of the proposed analog circuit in PSpice matches well with the findings the theoretical study. Our results yield the conclusion that coupling excitation-free oscillators of Duffing type in a ring topology can be seen as a useful approach to obtain multi-spiral chaotic attractors.

A Neuromorphic CMOS Circuit With Self-Repairing Capability.

Neurophysiological observations confirm that the brain not only is able to detect the impaired synapses (in brain damage) but also it is relatively capable of repairing faulty synapses. It has been shown that retrograde signaling by astrocytes leads to the modulation of synaptic transmission and thus bidirectional collaboration of astrocyte with nearby neurons is an important aspect of self-repairing mechanism. Specifically, the retrograde signaling via astrocyte can increase the transmission probability of the healthy synapses linked to the neuron. Motivated by these findings, in the present research, a CMOS neuromorphic circuit with self-repairing capabilities is proposed based on astrocyte signaling. In this way, the computational model of self-repairing process is hired as a basis for designing a novel analog integrated circuit in the 180-nm CMOS technology. It is illustrated that the proposed analog circuit is able to successfully recompense the damaged synapses by appropriately modifying the voltage signals of the remaining healthy synapses in the wide range of frequency. The proposed circuit occupies 7500- [Formula: see text] silicon area and its power consumption is about [Formula: see text]. This neuromorphic fault-tolerant circuit can be considered as a key candidate for future silicon neuronal systems and implementation of neurorobotic and neuro-inspired circuits.

Cardiac and respiratory signal extraction methods from ballistocardiography signal sensed using fiber bragg grating sensor

This work presents a simple, efficient and an easy-to-build ballistocardiography sys-tem using Fiber Bragg Grating (FBG) sensor and a comprehensive assessment of relevant digital signal processing algorithms to simultaneously extract respiratory and cardiac frequency components from a cluttered mix Ballistocardiography (BCG) signal. The primary purpose of the current study is two-fold: first- to build an analog circuit for BCG signal amplification, and second to evaluate the performance of three state-of-the-art methods, namely: lowpass-highpass filter, weiner filter and ensemble empherical mode decomposition to simultaneously extract respiratory and cardiac frequency components from the BCG signal. BCG measurements from test subjects were used in this study and a commercial digital stethoscope was used to validate the performance of methods used in this study. In addition to the effective amplification of the BCG signal through proposed analog circuit configuration, we demonstrate that a simple low pass high pass filter configuration can be used for accurate measurement of cardiac and respiratory frequencies. Due to its simplicity, the proposed system can be suitably tailored to process BCG signal for simultaneous extraction of respiration and heart rate which can aid as an effective diagnostic tool for identifying critical disorders associated with lungs and heart dysfunction.

An analog circuit model for drive mode of MEMS vibratory gyroscope

In this paper, an analog circuit model for the drive mode of a two-degree-of-freedom MEMS vibratory gyroscope is presented. This model is implemented on a printed circuit board by analog integrated circuits. To investigate the real behavior of the gyroscope sensor, the cubic stiffness coefficient is considered. This proposed circuit can be a suitable test bench for designers of gyroscope control loops. In other words, one can test and finalize gyroscope control loops before fabricating the gyroscope die. When we come to solve the gyroscope dynamic equations, there are some significantly important terms in response with small amplitudes. To make these signals vivid and noticeable in hardware implementation, the gyroscope coefficients are scaled to be measurable. The frequency response of the drive mode for various excitation signal amplitude is obtained. For large values of AC excitation, the hysteresis loop is appeared in the frequency response of the drive mode, while the frequency response of the proposed circuit model to the small AC excitation is Gaussian-shaped completely. However, the drive mode natural frequency variation versus the AC excitation signal amplitude variation is observed. The drive mode natural frequency increases nonlinearly with increasing the AC excitation signal amplitude. To verify the performance of the proposed analog circuit model, the dynamics equations of the MEMS vibratory gyroscope drive mode are simulated by MATLAB Simulink software. The comparison between the simulation and the experimental results indicates that the results are completely consistent. The proposed analog circuit can be an appropriate choice for presenting the real behavior of the MEMS vibratory gyroscope accurately.

Alternative of Bridge-Based Circuits for Differential Resistive Sensors

This paper presents an alternative approach to implement a signal conditioning circuit for measuring resistance relative changes of differential resistive sensors. The proposed analog circuit uses two operational conveyors and one operational amplifier (opamp) as active building blocks to produce an output voltage as a function of the relative change of the sensor. In comparison with the classic voltage-mode Wheatstone bridge (VMWB) configuration, the sensor relative change can be estimated by the proposed circuit without using any sensor reference resistor. Surpassing a current-mode Wheatstone bridge (CMWB) using second-generation current conveyors (CCIIs), the proposed configuration provides higher accuracy. Compared to existing mixed-mode configurations realized in integrated circuit form, the proposed circuit offers simpler construction. PSPICE simulation and experimental results are given to verify the effectiveness of the proposed circuit. Test results obtained by utilizing the implemented prototype for a commercial linear position sensor are also included.

Performance evaluation of analog circuit using improved LSSVR subject to data information uncertainty

This paper demystifies the proposed analog circuit performance evaluation methods based on improved LSSVR (ILSSVR) by examining the arithmetic speed and the evaluation reliability online. The ILSSVR performance evaluation scheme has the robustness for the signal information uncertainty, which may be deduced by nonlinear feature, time varying feature and contain faults value about industrial field data information. More specially, the self-update via incremental and reduced interaction is employed to detect the interests both on history data information and the updated data information, and the features extraction nonlinear independent component analysis (NICA) is proposed, then the number of the feature data is controlled and desired time consumed is guaranteed. In addition, the multi-kernel and weighted idea have also been employed to interfuse quite flexibility to the bandwidths of kernel online. The proposed analog circuit performance evaluation scheme ILSSVR is evaluated for two filter circuit: leapfrog filter circuit and self-adapting filter circuit. And the effectiveness is illustrated through a numerical example.

Determination of Thyroid Disorders in the Human Body using TSH, T3 and T4 Levels

This is an endeavour to simulate the concept of determining type of Thyroidism after stipulating the TSH, T3 and T4 levels in the human body by using proposed analog circuit. The Analog devices like operational amplifiers have behaviour similar to the mathematical operations. Till date there are so many software based techniques used for determination of effective dose to be provided to the patient so that normal level of Thyroxine can be maintained in the human body [1]. There is a need for hardware-oriented analog device to provide an accurate and efficient mean for calculation of effective dose amount and TSH, T3 and T4 values can be used. Basically, the voltages in the high-gain dc amplifiers are equated to these three variables and the operational amplifiers can do the mathematical operations on the voltages, although the accuracy of measuring voltage is limited to certain point. The simulation has been done using CircuitMaker.

Synchronization of electronic genetic networks

We describe a simple analog electronic circuit that mimics the behavior of a well-known synthetic gene oscillator, the repressilator, which represents a set of three genes repressing one another. Synchronization of a population of such units is thoroughly studied, with the aim to compare the role of global coupling with that of global forcing on the population. Our results show that coupling is much more efficient than forcing in leading the gene population to synchronized oscillations. Furthermore, a modification of the proposed analog circuit leads to a simple electronic version of a genetic toggle switch, which is a simple network of two mutual repressor genes, where control by external forcing is also analyzed.

A clustering/labeling analog LSI architecture for media recognition

AbstractClustering and labeling are basic processes in speech and image recognition. In this paper, we present the design of an analog circuit for a clustering and labeling system and the performance evaluation results based on a simulation. The number of basic computation modules becomes huge when digital LSIs are designed for parallel processing. It becomes one reason for the increase in the chip area. Therefore, we propose an architecture for a clustering/labeling circuit. It introduces the similarity circuit that utilizes the fundamental characteristics of MOS and the C matrix circuit that outputs the results of the matrix computation. We use this circuit to conduct a circuit simulation that includes statistical analysis and confirm the ability to perform feature clustering of simple speech. The proposed analog circuit has an extremely simple architecture and is expected to decrease the chip area by about 1/36 compared to an 8‐bit digital design. © 2002 Wiley Periodicals, Inc. Electron Comm Jpn Pt 3, 85(10): 1–7, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ecjc.1120

A high-speed neural analog circuit for computing the bit-level transform image coding

This paper presents a Hopfield-type neural network approach which leads to an analog circuit for implementing the bit-level transform image. Different from the conventional digit al approach to image coding, the analog coding system would operate at a much higher speed and require less hardware than digital system. In order to utilize the concept of neural net, the computation of a two-dimensional DCT-based transform coding should be reformulated as minimizing a quadratic nonlinear programming problem subject to the corresponding 2's complement binary variables of 2-D DCT coefficients. A novel Hopfield-t ype neural net with a number of graded-response neurons designed to perform the quadratic nonlinear programming would lead to such a solution in a time determined by RC time constants, not by algorithmic time complexity. A fourth order Runge-Kutt a simulation is conducted to verify the performance of the proposed analog circuit. Experiments show that the circuit is quite robust and independent of parameter variations and the comput ation time of 8 x 8 DCT is about ins. In practice, programmable hybrid digital-analog MOS circuits are required to implement the neural-based DCT optimizer. The circuit techniques are based on extremely simple and programmable analog parameterized MOS modules with such attractive features as reconfigurability, input/output compatibility, and unrestricted fan-in/fan-out capability.