Bibliografie tematiche / Analog-to-feature converter

Letteratura scientifica selezionata sul tema "Analog-to-feature converter"

Autore: Grafiati

Pubblicato: 1 giugno 2024

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Articoli di riviste sul tema "Analog-to-feature converter":

Back, Antoine, Paul Chollet, Olivier Fercoq e Patricia Desgreys. "Power-aware feature selection for optimized Analog-to-Feature converter". Microelectronics Journal 122 (aprile 2022): 105386. http://dx.doi.org/10.1016/j.mejo.2022.105386.

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Agarwal, Ritika, e Sameer Sonkusale. "Input-Feature Correlated Asynchronous Analog to Information Converter for ECG Monitoring". IEEE Transactions on Biomedical Circuits and Systems 5, n. 5 (ottobre 2011): 459–67. http://dx.doi.org/10.1109/tbcas.2011.2116787.

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Zhao, Ying Kai, Liang Yin, Zhao Tong Liu, Wei Ping Chen e Xiao Wei Liu. "A 16 Bits 500 kHz Sigma-Delta DAC for Silicon Micro Gyroscope". Key Engineering Materials 645-646 (maggio 2015): 605–9. http://dx.doi.org/10.4028/www.scientific.net/kem.645-646.605.

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In this paper, a 16 Bits 500 kHz Sigma-Delta DAC for Silicon Micro Gyroscope is proposedin order to enhance the precision of the digital to analog converter level.The interpolation filterhas achieved 64 times interpolation function,using three cascaded manner, it employs three level cascaded of FIR filterstructure. It achieves a 64 times oversampling feature. The signalbandwidth of the designs interpolation filter is 100 kHz, SNR reach 106dB. Fifth-order single-loop structure CIFB achieve noise shaping modulator function to verify the stability of the system, after the completion of CSD coefficient coding, signal to noise ratio reached 119.7dB, effective bits reached 19.59. The switched capacitor technology actualize analog reconstruction filter module, and using a typically switched capacitor DAC achieved high jump "0, 1" digital signal is converted into an analog signal, the digital-analog conversion achieved.

Manokhin, Mikhail, Paul Chollet e Patricia Desgreys. "Towards Flexible and Low-Power Wireless Smart Sensors: Reconfigurable Analog-to-Feature Conversion for Healthcare Applications". Sensors 24, n. 3 (3 febbraio 2024): 999. http://dx.doi.org/10.3390/s24030999.

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Analog-to-feature (A2F) conversion based on non-uniform wavelet sampling (NUWS) has demonstrated the ability to reduce energy consumption in wireless sensors while employed for electrocardiogram (ECG) anomaly detection. The technique involves extracting only relevant features for a given task directly from analog signals and conducting classification in the digital domain. Building on this approach, we extended the application of the proposed generic A2F converter to address a human activity recognition (HAR) task. The performed simulations include the training and evaluation of neural network (NN) classifiers built for each application. The corresponding results enabled the definition of valuable features and the hardware specifications for the ongoing complete circuit design. One of the principal elements constituting the developed converter, the integrator brought from the state-of-the-art design, was modified and simulated at the circuit level to meet our requirements. The revised value of its power consumption served to estimate the energy spent by the communication chain with the A2F converter. It consumes at least 20 and 5 times less than the chain employing the Nyquist approach in arrhythmia detection and HAR tasks, respectively. This fact highlights the potential of A2F conversion with NUWS in achieving flexible and energy-efficient sensor systems for diverse applications.

Triwiyanto, T., Endro Yulianto, I. Dewa Gede Hari Wisana, Muhammad Ridha Mak’ruf, Bambang Guruh Irianto, Endang Dian Setioningsih, Ridho Hanggara Mukti e Dhimas Sugma Herdinanta. "Electromyography Feature Analysis to Recognize the Hand Motion in a Prosthetic Hand Design". Journal of Biomimetics, Biomaterials and Biomedical Engineering 50 (aprile 2021): 25–37. http://dx.doi.org/10.4028/www.scientific.net/jbbbe.50.25.

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The increasing need for prosthetic hands for people with disabilities is one reason for innovation in the field of prosthetic hands to create the best prosthetic hand technology. In the design of EMG-based prosthetic hands, this is determined by several things, among others, the selection of features. The selection of the right features will determine the accuracy of the prosthetic hand Therefore, the purpose of this study is to analysis the time domain feature to obtain the best feature in classifying the hand motion. The contribution of this work is able to detect 4 movements in real time, namely hand close, flexion, extension, and relax. The Electromyograph signal is tapped using an electromyograph (EMG) dry electrode sensor in which there is a circuit of EMG instrumentation amplifier. Furthermore, the analog EMG signal data is processed through the ADC (Analog to Digital Converter) by using MCP3008 device. EMG signal data is processed in Raspberry Pi. A feature extraction process is applied to reduce data and determine the characteristics of each hand movement. Feature extraction used is MAV (mean absolute value), SSI (sign slope integral), VAR (variance), and RMS (root mean square). From the results of the four-time domain feature, then the best feature extraction is determined using scatter plot and Euclidean distance. The results that have been carried out on ten people with each person doing ten sets of movements (hand close, flexion, extension, relax), showing the best Euclidean distance results, is the RMS feature, with a value of 2608.07. This data is the result of the best feature extraction analysis through the method of calculating the distance of feature extraction data using Euclidean distance. This analysis of time domain feature is expected to be useful for further experiment in machine learning implementation so that it can be obtained an effective prosthetic hand.

Sahu, Anil Kumar, Vivek Kumar Chandra e G. R. Sinha. "Analysis of Quantization Noise and Power Estimation of Continuous-Time Delta Sigma Analog-to-Digital Converter Using Test Enable Feature For 4G Radios". International Journal of Informatics and Communication Technology (IJ-ICT) 7, n. 2 (1 agosto 2018): 82. http://dx.doi.org/10.11591/ijict.v7i2.pp82-88.

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<span>This paper presents a novel approach for completely test enable feature and low-voltage delta– sigma analog-to-digital (A/D) converters for cutting edge wireless applications. Oversampling feature of ADCs and DACs is enough to meet the requirement related to in-band and adjacent channel leakage ratio (ACLR) execution of 3G/4G portable radio. The quantization noise which is not filtered in ADC is addressed. We have achieved work power-optimization and test enable feature of oversampling ADC is uses in design and simulation so that the problem of quantization error in continues time sigma delta ADC is solved. This paper suggests support to designer for selecting appropriate topologies with various channel arrangements, number of bits and oversampling issues. A test enable feature of CT A/D is presented introducing the test signal generation (TSG) and the COrdinate Rotation Digital Computer (CORDIC) for evaluating the performance of ADC. This helps in addressing the challenge of 4G and upcoming 5G wireless radio. System level plan of a delta–sigma modulator ADC for 4G radios is studied</span><span lang="IN">.</span>

Van den Bossche, Alex, Ekaterina Dimitrova, Vencislav Valchev e Firgan Feradov. "A simplified controller and detailed dynamics of constant off-time peak current control". Journal of Electrical Engineering 68, n. 5 (1 settembre 2017): 390–95. http://dx.doi.org/10.1515/jee-2017-0072.

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Abstract A fast and reliable current control is often the base of power electronic converters. The traditional constant frequency peak control is unstable above 50 % duty ratio. In contrast, the constant off-time peak current control (COTCC) is unconditionally stable and fast, so it is worth analyzing it. Another feature of the COTCC is that one can combine a current control together with a current protection. The time dynamics show a zero-transient response, even when the inductor changes in a wide range. It can also be modeled as a special transfer function for all frequencies. The article shows also that it can be implemented in a simple analog circuit using a wide temperature range IC, such as the LM2903, which is compatible with PV conversion and automotive temperature range. Experiments are done using a 3 kW step-up converter. A drawback is still that the principle does not easily fit in usual digital controllers up to now.

Kim, Keonwook, e Yujin Hong. "Gaussian Process Regression for Single-Channel Sound Source Localization System Based on Homomorphic Deconvolution". Sensors 23, n. 2 (9 gennaio 2023): 769. http://dx.doi.org/10.3390/s23020769.

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To extract the phase information from multiple receivers, the conventional sound source localization system involves substantial complexity in software and hardware. Along with the algorithm complexity, the dedicated communication channel and individual analog-to-digital conversions prevent an increase in the system’s capability due to feasibility. The previous study suggested and verified the single-channel sound source localization system, which aggregates the receivers on the single analog network for the single digital converter. This paper proposes the improved algorithm for the single-channel sound source localization system based on the Gaussian process regression with the novel feature extraction method. The proposed system consists of three computational stages: homomorphic deconvolution, feature extraction, and Gaussian process regression in cascade. The individual stages represent time delay extraction, data arrangement, and machine prediction, respectively. The optimal receiver configuration for the three-receiver structure is derived from the novel similarity matrix analysis based on the time delay pattern diversity. The simulations and experiments present precise predictions with proper model order and ensemble average length. The nonparametric method, with the rational quadratic kernel, shows consistent performance on trained angles. The Steiglitz–McBride model with the exponential kernel delivers the best predictions for trained and untrained angles with low bias and low variance in statistics.

Yeh, Yun Chi, Tsung Fu Chien, Cheng Yuan Chang e Tsui Shiun Chu. "A Mahalanobis Distance Measurement Method to Analyze Current Waveform for Determining the Motor’s Quality Types". Applied Mechanics and Materials 870 (settembre 2017): 317–22. http://dx.doi.org/10.4028/www.scientific.net/amm.870.317.

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This study proposes a Mahalanobis Distance Measurement (MDM) method to analyze current waveform for determining the motor’s quality types. The MDM method consists of three major stages: (i) the preprocessing stage which is for enlarging motor current waveforms’ amplitude and eliminating noises, and includes signal amplitude amplifier, filter circuit (eliminating noises), and analog-to-digital converter (ADC) parts, (ii) the qualitative features stage which is for qualitative feature selection on motor current waveforms, and (iii) the classification stage which is for determining motor quality types using the MDM method. It can recognize defective motors and their defective types in less than 0.5 second. In the experiment, the total classification accuracy (TCA) was approximately 99.03% in average. The proposed method has the advantages of good detection results, no complex mathematic computations, hi-speed, and hi-reliability.

Fang, Ni, Dong Wang, Xiangming Sun, Chaosong Gao, Ran Chen, Zhuo Zhou, Shiqiang Zhou, Cheng Lian e Zijian Lang. "50.3 ps time resolution and an 11-channel time measuring chip for Topmetal detectors". Journal of Instrumentation 19, n. 03 (1 marzo 2024): C03047. http://dx.doi.org/10.1088/1748-0221/19/03/c03047.

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Abstract The Topmetal detector, utilized in this investigation, is a direct-type CMOS pixel sensor known for its distinctive feature of employing exposed metal at the top of each pixel to directly capture external charged particles. This method generates electrical signals through the induction of charge. At present, it is mainly used in gas pixel detector(GPD) and particle beam monitoring. In this paper, we present a new front-end design aimed at enhancing the capabilities of the Topmetal pixel detector. The focus is on incorporating a Time-Digital Conversion (TDC) ASIC into the front-end, with the objective of achieving high-precision time measurement in addition to superior position resolution. The function of the TDC is achieved by the two reverse delay chains, 11 edge acquisition circuits Time-to-Amplitude Converter (TAC), analog gate, weight count module, and Wilkinson Analog-to-Digital Converter (ADC). Coarse time measurement is implemented based on a counter with a working frequency of 500 MHz, and fine time measurement is implemented by the combination of TAC and ADC. The design prototype was taped out with the GSMCR130 nm technology. Test results show that this circuit can handle up to 11 consecutive cases, with the minimum time interval of adjacent cases being 500 ps and the bin size up to 2 ps. The time measurement precision is better than 50.3 ps RMS and the PVT(Process Voltage Temperature) robustness of the input delay chain circuit is validated, showing the stable performance of the design.

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Tesi sul tema "Analog-to-feature converter":

Back, Antoine. "Conception et intégration d'un convertisseur analogique-paramètres flexible pour les capteurs intelligents". Electronic Thesis or Diss., Institut polytechnique de Paris, 2022. http://www.theses.fr/2022IPPAT020.

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Avec le fort développement de l'Internet des Objets (IoT), il devient nécessaire de converger vers de nouveaux capteurs dit intelligents. Ces capteurs doivent permettre d'analyser l'environnement extérieur, comprendre le contexte dans lequel ils sont utilisés et être conscient des besoins utilisateurs. Ils doivent cependant rester petits, fiables, bon marché et avoir une autonomie de plusieurs années. La conversion analogique-paramètre (Analog-to-Feature, A2F) est une nouvelle méthode d'acquisition pensée pour les appareils IoT, et semble être une solution adaptée pour de tels capteurs. Cette conversion consiste à extraire des paramètres directement sur le signal analogique. Une sélection pertinente des paramètres permet d'extraire uniquement l'information nécessaire à une tache particulière. Le convertisseur proposé est basé sur la technique de l'échantillonnage non-uniforme en ondelettes (NUWS). L'architecture mélange le signal analogique avec des ondelettes paramétrables avant d'intégrer et convertir le signal en données numériques. L'objectif de la thèse est de proposer une méthode pour concevoir un convertisseur A2F générique basé sur le NUWS. Il est ainsi nécessaire de définir les caractéristiques des ondelettes afin d'acquérir une large gamme de signaux basse fréquence (ECG, EMG, EEG, parole…). Cette étape nécessite l'utilisation d'algorithmes de sélection de paramètres et d'algorithmes d'apprentissage automatique pour sélectionner le meilleur ensemble d'ondelettes pour une application donnée et qui doit permettre de définir les spécifications du convertisseur. L'étape de sélection des paramètres doit tenir compte des contraintes de mise en œuvre pour optimiser au mieux la consommation d'énergie. Un algorithme de sélection de paramètres est proposé pour choisir des ondelettes pour une application donnée, afin de maximiser la précision de classification tout en diminuant la consommation d'énergie, grâce à un modèle de consommation réalisé dans une technologie CMOS 0.18μm
The Internet of Things (IoT) is currently experiencing huge developments. IoT includes lots of different devices such as Wireless Sensors Networks (WSN) or wearable electronics that rely on wireless communications. These networks need to understand the context in which they are used. This mean that the system must know what is happening around it, i.e. sense the environment, and understands the needs of the user. This requires always-on sensing on many sensors while being small, cheap, reliable and having a lifetime of several years. Analog-to-Feature (A2F) conversion is a new acquisition method that was thought for IoT devices. The converter aims at extracting useful features directly on the analog signal. By carefully choosing a set of features, it is possible to acquire only the relevant information for a given task. The proposed converter is based on the Non-Uniform Wavelet Sampling (NUWS) architecture. The architecture mixes the analog signal with tunable wavelets prior to integration and digital conversion. The aim of the thesis is to propose a method to design a generic A2F converter based on the NUWS. It includes the definition of the wavelet parameters in order to acquire a broad range of low frequency signals (ECG, EMG, EEG, speech …). This step requires the use of feature selection algorithms and machine learning algorithms for selecting the best set of wavelets for a given application and should be used to define the specifications for the converter. The feature selection step must be aware of physical implementation constraints to optimize energy consumption as much as possible. A feature selection algorithm is proposed to choose wavelets for a given application, in order to maximize classification accuracy while decreasing power consumption, through a power model designed in CMOS 0.18μm

Libri sul tema "Analog-to-feature converter":

Piepenburg, Scott. Digitizing Audiovisual and Nonprint Materials. ABC-CLIO, LLC, 2015. http://dx.doi.org/10.5040/9798400640674.

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Abstract (sommario):

AV collections in libraries are disintegrating, and their playback equipment is soon to be obsolete. Digitizing can be the solution to decay and for continued access. Why give up on at-risk treasures of your AV collection when you can easily digitize them in house? This guide walks you through the process of planning and implementing digitization projects for the common formats libraries have collected over the last 30 or 40 years. It guides first-time users in setting up a facility to convert analog tapes and records into a digital form, explaining how to clean up those sources to produce a high-quality output for end-users. The same theories and skills are applied to the visual domain so you can convert VHS, Beta, U-Matic, and laserdiscs into archival visual formats. A unique feature of the book is that it will help you understand the process without having to become a techno-geek. Basic information on computer hardware and software is discussed, including the equipment needed to digitize various formats. Techniques for capturing, editing, storing, and making digitized files available to patrons are also covered. Because budgets are always a concern, the work looks at ways you can leverage current resources and facilities with minimal outlay of capital to start a project, and it offers practical guidance on how to maintain the information long term.

Capitoli di libri sul tema "Analog-to-feature converter":

Octavian Nemeș, Raul, Mircea Ruba, Sorina Maria Ciornei e Raluca Maria Raia. "Powerful Multilevel Simulation Tool for HiL Analysis of Urban Electric vehicle’s Propulsion Systems". In New Perspectives on Electric Vehicles [Working Title]. IntechOpen, 2021. http://dx.doi.org/10.5772/intechopen.98532.

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The general focus of the proposed chapter is to describe a complex yet transparent solution for advanced simulation analysis of urban electric vehicles propulsion unit. As general rule, precise and realistic results are obtained only when performing real-time simulations, engaging dedicated software for such applications. Hence, simulation of an electric vehicle as a complete solution can become rather difficult. The authors targeted advanced analysis of the propulsion unit, including the motor, the battery, the power converter, and its control. These are designed using multilevel models in Matlab/Simulink, referring to different complexity levels of each assembly. Another feature of the models is their organization, based on Energetic Macroscopic Representation (EMR), this easing the process of inter-connecting models correctly. Nevertheless, the mechanical, aerodynamical and road profile details are included using Amesim Software. All the simulations are performed on a real-time target, using a National Instruments PXIe embedded controller. The latter runs NI VeriStand software, allowing real-time communication between Amesim and Simulink offering in the same time possibility to read/write analog/digital IOs for external communication. This feature in fact is used when passing from modeling to Hardware in the Loop (HIL) analysis, replacing the simulated assembly with the actual one.

Atti di convegni sul tema "Analog-to-feature converter":

Back, Antoine, Paul Chollet, Olivier Fercoq e Patricia Desgreys. "Feature selection algorithms for flexible analog-to-feature converter". In 2020 18th IEEE International New Circuits and Systems Conference (NEWCAS). IEEE, 2020. http://dx.doi.org/10.1109/newcas49341.2020.9159817.

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Manokhin, Mikhail, Paul Chollet e Patricia Desgreys. "Flexible Analog-to-Feature Converter for Wireless Smart Healthcare Sensors". In 2023 21st IEEE Interregional NEWCAS Conference (NEWCAS). IEEE, 2023. http://dx.doi.org/10.1109/newcas57931.2023.10198150.

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Tang, Xiaochen, Shanshan Liu, Wenjie Che e Wei Tang. "Tampering Attack Detection in Analog to Feature Converter for Wearable Biosensor". In 2022 IEEE International Symposium on Circuits and Systems (ISCAS). IEEE, 2022. http://dx.doi.org/10.1109/iscas48785.2022.9937707.

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Tang, Xiaochen, Qisong Hu e Wei Tang. "Analog to Digital Feature Converter based on Oversampling Modulators for ECG Delineation". In 2019 IEEE 62nd International Midwest Symposium on Circuits and Systems (MWSCAS). IEEE, 2019. http://dx.doi.org/10.1109/mwscas.2019.8885145.

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del Campo, Sergio Martin, Kim Albertsson, Joakim Nilsson, Jens Eliasson e Fredrik Sandin. "FPGA prototype of machine learning analog-to-feature converter for event-based succinct representation of signals". In 2013 IEEE International Workshop on Machine Learning for Signal Processing (MLSP). IEEE, 2013. http://dx.doi.org/10.1109/mlsp.2013.6661996.

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Chakrabartty, Shantanu. "Multiple-input multiple-output (MIMO) analog-to-feature converter chipsets for sub-wavelength acoustic source localization and bearing estimation". In SPIE Defense, Security, and Sensing, a cura di Edward M. Carapezza. SPIE, 2010. http://dx.doi.org/10.1117/12.852671.

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Swope, C. H., J. G. Link e D. G. Haugen. "Multichannel optical system for a medical diagnostic analyzer". In OSA Annual Meeting. Washington, D.C.: Optica Publishing Group, 1992. http://dx.doi.org/10.1364/oam.1992.thv4.

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An optical analyzer has been developed to monitor biochemical reactions that are used in diagnostic tests, which are typically conducted in clinical hemostasis–thrombosis laboratories. The module measures changes in the optical transmission of up to 15 samples simultaneously at 35 wavelength bands from 395 to 710 nm. The full spectrum transmission data for all samples are collected five times per second. This is accomplished with the use of a 50 W tungsten halogen lamp and holographic diffraction gratings that produce a first order transmission spectrum across a 40 element linear array of Si detectors. A rotating shutter device makes it possible to use only five detector arrays for monitoring all 15 samples. The arrays are scanned synchronously with the rotating shutter. Signals from the diodes are integrated over time through a charge coupled amplifier. The gratings are used under the Bragg condition with an angular dispersion of 0.07°/nm in the first order and with peak efficiencies exceeding 50% at 475 nm. A digital to analog converter is used with the amplifiers to provide a variable gain for each detector element. This feature is used to normalize and optimize the detectors’ output signals.

Guo, Chencheng, Hui Qian e Baoling Hong. "Feature-Based Sensing Matrix Design for Analog to Information Converters". In ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2022. http://dx.doi.org/10.1109/icassp43922.2022.9747114.

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Chakrabartty, Shantanu, e Amit Gore. "Sigma-delta analog to LPC feature converters for portable recognition interfaces". In 2009 IEEE International Symposium on Circuits and Systems - ISCAS 2009. IEEE, 2009. http://dx.doi.org/10.1109/iscas.2009.5118352.

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Sleiman, Nicolas, e Julie A. Reyer. "HIL Simulation of a Track Type Tractor for Autonomous Controller Testing". In ASME 2008 Dynamic Systems and Control Conference. ASMEDC, 2008. http://dx.doi.org/10.1115/dscc2008-2210.

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The mining industry is introducing several autonomous mining operations, however the development of these algorithms is extremely expensive. This paper discusses the integration of a Hardware In the Loop (HIL) simulation to earthmoving equipment to aid in the development of autonomous mining operations. The benefit of this simulation is to save time and money for engineers developing the autonomous features. The hardware setup contained machine components that were connected to the Electronic Control Modules (ECMs). The ECMs used in the lab setup were the same as those on the actual tract type tractors. Those ECMs receive input signals based on which they command the solenoids. The HIL simulator converts the analog outputs into digital ones. Then the HIL sends out digital or simulated outputs to the ECMs such as pressure and fuel levels. The results of this work compare simulated data and real machine test data of an autonomous feature. A comparison is presented between the autonomous feature and a human operator. Finally potential of the HIL is demonstrated examining the autonomous feature with different soil conditions.