Marcel Jacomet

Layout-dependent fault analysis and test synthesis for CMOS circuits

An arithmetic approach to extract the potential physical defects from the specific circuit layout of an integrated circuit is proposed. The defects subsequently are transformed into circuit faults and weighted according to their likelihood of occurrence. Based on these open and short faults extracted from CMOS layouts, an automatic test pattern generator is implemented. The test synthesis of some combinational CMOS benchmark circuits illustrates the superiority of the CMOS fault models and their application to test pattern generation as compared with the classical stuck-at fault models. >

Fantestic: towards a powerful fault analysis and test pattern generator for integrated circuits

A methodology relating physical defects to the circuit-level faulty behavior caused by these defects and a fast algebraic implementation to provide a realistic fault list are proposed. In conjunction with the obtained statistical data on the likelihood of each fault and the knowledge of its best observable electrical manifestation, a solid basis for an effective and powerful test pattern generation is provided. To achieve an accurate modeling of bridging faults, a novel fault model, the large-scope short, is developed and implemented. In contrast to other fault analysis procedures which use time-consuming simulation methods to generate or induce physical defects, the proposed Fantestic methodology is very fast in extracting defects and converting them to a ranked fault list. The analysis of some sample CMOS circuits illustrates the effect of different physical defects on circuit-level faults.<<ETX>>

On-line optimization of fuzzy systems

Fuzzy controlled systems are considered and an on-line adaptation of fuzzy parameters is implemented. A description of the design of an optimization procedure is given. Selection criteria for optimization algorithms are defined and a Downhill Simplex algorithm is carefully examined.

Esophageal Long-Term ECG Reveals Paroxysmal Atrial Fibrillation

A 79-year-old man was referred for coronary angiography because of atypical chest pain. The patients medical history included a myocardial infarction 5 years previously and well-controlled arterial hypertension. Three months before this admission he reported atypical chest pain, sometimes associated with palpitations lasting seconds up to a few minutes. Hence, he underwent ambulant 24-hour ECG, which revealed frequent atrial premature beats but no other arrhythmia. On admission, the patient was in sinus rhythm. Echocardiography showed normal ventricular function without structural heart disease. After successful percutaneous transluminal coronary angioplasty, the patient was included in a study …

Comparing Signal Processing Hardware-Synthesis Methods Based on the Matlab Tool-Chain

Various commercial and academic tools are available for the synthesis of hardware algorithms. Focusing on signal processing algorithms, we compare efficiency, flexibility and usability of hardware synthesis approaches based on the widely used Matlab with add-on toolboxes or 3rd-party tools. We use several designs as case studies to investigate the effect of the tool features with respect to hardware architecture and design flexibility. Special emphasis is set to the designers freedom of choice between different arithmetic operator architectures, between pipe-lining versus operator sequencing, and between parallel versus sequential architectures.

Electrodes for Long-Term Esophageal Electrocardiography

The emerging application of long-term and high-quality ECG recording requires alternative electrodes to improve the signal quality and recording capability of surface skin electrodes. The esophageal ECG has the potential to overcome these limitations but necessitates novel recorder and lead designs. The electrode material is of particular interest, since the material has to ensure conflicting requirements like excellent biopotential recording properties and inertness. To this end, novel electrode materials like PEDOT and silver-PDMS as well as established electrode materials such as stainless steel, platinum, gold, iridium oxide, titanium nitride, and glassy carbon were investigated by long-term electrochemical impedance spectroscopy and model-based signal analysis using the derived in vitro interfacial properties in conjunction with a dedicated ECG amplifier. The results of this novel approach show that titanium nitride and iridium oxide featuring microstructured surfaces did not degrade when exposed to artificial acidic saliva. These materials provide low electrode potential drifts and insignificant signal distortion superior to surface skin electrodes making them compatible with accepted standards for ambulatory ECG. They are superior to the noble and polarizable metals such as platinum, silver, and gold that induced more signal distortions and are superior to esophageal stainless steel electrodes that corrode in artificial saliva. The study provides rigorous criteria for the selection of electrode materials for prolonged ECG recording by combining long-term in vitro electrode material properties with ECG signal quality assessment.

Graphics Processor Unit Based Parallelization of Optimized Baseline Wander Filtering Algorithms for Long-term Electrocardiography

Long-term electrocardiogram (ECG) often suffers from relevant noise. Baseline wander in particular is pronounced in ECG recordings using dry or esophageal electrodes, which are dedicated for prolonged registration. While analog high-pass filters introduce phase distortions, reliable offline filtering of the baseline wander implies a computational burden that has to be put in relation to the increase in signal-to-baseline ratio (SBR). Here, we present a graphics processor unit (GPU)-based parallelization method to speed up offline baseline wander filter algorithms, namely the wavelet, finite, and infinite impulse response, moving mean, and moving median filter. Individual filter parameters were optimized with respect to the SBR increase based on ECGs from the Physionet database superimposed to autoregressive modeled, real baseline wander. A Monte-Carlo simulation showed that for low input SBR the moving median filter outperforms any other method but negatively affects ECG wave detection. In contrast, the infinite impulse response filter is preferred in case of high input SBR. However, the parallelized wavelet filter is processed 500 and four times faster than these two algorithms on the GPU, respectively, and offers superior baseline wander suppression in low SBR situations. Using a signal segment of 64 mega samples that is filtered as entire unit, wavelet filtering of a seven-day high-resolution ECG is computed within less than 3 s. Taking the high filtering speed into account, the GPU wavelet filter is the most efficient method to remove baseline wander present in long-term ECGs, with which computational burden can be strongly reduced.

An Efficient Hardware Implementation for a Reciprocal Unit

The computation of the reciprocal of a numerical value is an important ingredient of many algorithms. We present a compact hardware architecture to compute reciprocals by two or three Newton-Raphson iterations to obtain the accuracy of IEEE 754 single- and double-precision standard, respectively. We estimate the initialization value by a specially designed second-order polynomial approximating the reciprocal. By using a second-order polynomial, we succeed in using one single hardware architecture for both, the polynomial approximation computations as well as the Newton-Raphson iterations. Therefore, we obtain a most compact hardware implementation for the complete reciprocal computation.

A Baseline Wander Tracking System for Artifact Rejection in Long-Term Electrocardiography

Long-term electrocardiogram (ECG) signals might suffer from relevant baseline disturbances during physical activity. Motion artifacts in particular are more pronounced with dry surface or esophageal electrodes which are dedicated to prolonged ECG recording. In this paper we present a method called baseline wander tracking (BWT) that tracks and rejects strong baseline disturbances and avoids concurrent saturation of the analog front-end. The proposed algorithm shifts the baseline level of the ECG signal to the middle of the dynamic input range. Due to the fast offset shifts, that produce much steeper signal portions than the normal ECG waves, the true ECG signal can be reconstructed offline and filtered using computationally intensive algorithms. Based on Monte Carlo simulations we observed reconstruction errors mainly caused by the non-linearity inaccuracies of the DAC. However, the signal to error ratio of the BWT is higher compared to an analog front-end featuring a dynamic input ranges above 15 mV if a synthetic ECG signal was used. The BWT is additionally able to suppress (electrode) offset potentials without introducing long transients. Due to its structural simplicity, memory efficiency and the DC coupling capability, the BWT is dedicated to high integration required in long-term and low-power ECG recording systems.

Bufferless Compression of Asynchronously Sampled ECG Signals in Cubic Hermitian Vector Space

Asynchronous level crossing sampling analog-to-digital converters (ADCs) are known to be more energy efficient and produce fewer samples than their equidistantly sampling counterparts. However, as the required threshold voltage is lowered, the number of samples and, in turn, the data rate and the energy consumed by the overall system increases. In this paper, we present a cubic Hermitian vector-based technique for online compression of asynchronously sampled electrocardiogram signals. The proposed method is computationally efficient data compression. The algorithm has complexity O(n), thus well suited for asynchronous ADCs. Our algorithm requires no data buffering, maintaining the energy advantage of asynchronous ADCs. The proposed method of compression has a compression ratio of up to 90% with achievable percentage root-mean-square difference ratios as a low as 0.97. The algorithm preserves the superior feature-to-feature timing accuracy of asynchronously sampled signals. These advantages are achieved in a computationally efficient manner since algorithm boundary parameters for the signals are extracted a priori.