arXiv subjects

Amit Kumar Mishra

Publications and source records attributed to Amit Kumar Mishra.

At least 37 records · Page 2Linked to original sources

arXiv2019

Low-cost spectrogram based counterfeit medicine detection

Contaminated substances such as counterfeit medication and food contami-nated with pesticide residue is a pandemic of utmost urgency. Spectroscopy and chromatography methods are often used but are expensive and complex and as such a need exists for a device that can be easily operated in developing commu-nities. We present a hacked visible spectrometer based contaminated substance detector using machine learning. The Support Vector Machine (SVM), Logistic Regression, linear Regression and Convolutional Neural Network (CNN) models have been implemented and are trained on the acquired spectrum data. Our results show that a lowcost method of identifying contaminated substances is achievable with very high accuracy.

eess.SP↗

arXiv2018

WEBCA: Weakly-Electric-Fish Bioinspired Cognitive Architecture

Neuroethology has been an active field of study for more than a century now. Out of some of the most interesting species that has been studied so far, weakly electric fish is a fascinating one. It performs communication, echo-location and inter-species detection efficiently with an interesting configuration of sensors, neu-rons and a simple brain. In this paper we propose a cognitive architecture inspired by the way these fishes handle and process information. We believe that it is eas-ier to understand and mimic the neural architectures of a simpler species than that of human. Hence, the proposed architecture is expected to both help research in cognitive robotics and also help understand more complicated brains like that of human beings.

cs.AI↗

arXiv2017

GSM-CommSense-based through-the-wall sensing

We have recently proposed a scheme to use the channel equalization blocks of telecommunication systems to sense changes in an environment. We call this communication-sensing, CommSense for short. After some initial positive results we tried to use our global system for mobile communication (GSM) based CommSense system for a through-the-wall sensing application. As the system was inherently highly under-determined we used statistical machine learning techniques to help us sense environmental changes in the behind-the-wall experiments. We observed that with limited amount of data per GSM frame of 577 μs a person can be detected across a wall to an accuracy of 77.458% and a person carrying a weapon can be detected to an accuracy of 95.208%. We present details of the experiments and the encouraging results that we have obtained in this article.

eess.SP↗

arXiv2017

ICABiDAS: Intuition Centred Architecture for Big Data Analysis and Synthesis

Humans are expert in the amount of sensory data they deal with each moment. Human brain not only analyses these data but also starts synthesizing new information from the existing data. The current age Big-data systems are needed not just to analyze data but also to come up new interpretation. We believe that the pivotal ability in human brain which enables us to do this is what is known as "intuition". Here, we present an intuition based architecture for big data analysis and synthesis.

cs.AI↗

arXiv2017

Mesh Model (MeMo): A Systematic Approach to Agile System Engineering

Innovation and entrepreneurship have a very special role to play in creating sustainable development in the world. Engineering design plays a major role in innovation. These are not new facts. However this added to the fact that in current time knowledge seem to increase at an exponential rate, growing twice every few months. This creates a need to have newer methods to innovate with very little scope to fall short of the expectations from customers. In terms of reliable designing, system design tools and methodologies have been very helpful and have been in use in most engineering industries for decades now. But traditional system design is rigorous and rigid. As we can see, we need an innovation system that should be rigorous and flexible at the same time. We take our inspiration from biosphere, where some of the most rugged yet flexible plants are creepers which grow to create mesh. In this thematic paper we shall explain our approach to system engineering which we call the MeMo (Mesh Model) that fuses the rigor of system engineering with the flexibility of agile methods to create a scheme that can give rise to reliable innovation in the high risk market of today.

cs.SE↗

arXiv2017

GSM based CommSense system to measure and estimate environmental changes

Facilitating the coexistence of radar systems with communication systems has been a major area of research in radar engineering. The current work presents a new way to sense the environment using the channel equalization block of existing communication systems. We have named this system CommSense. In the current paper we demonstrate the feasibility of the system using Global System for Mobile Communications (GSM) signals. The implementation has been done using open-source Software Defined Radio (SDR) environment. In the preliminary results obtained in our work we show that it is possible to distinguish environmental changes using the proposed system. The major advantage of the system is that it is inexpensive as channel estimation is an inherent block in any communication system and hence the added cost to make it work as an environment sensor is minimal. The major challenge, on which we are continuing our work, is how to characterize the features in the environmental changes. This is an acute challenge given the fact that the bandwidth available is narrow and the system is inherently a forward looking radar. However the initial results, as shown in this paper, are encouraging and we intend to use an application specific instrumentation (ASIN) scheme to distinguish the environmental changes.

cs.OH↗

arXiv2017

A DIKW Paradigm to Cognitive Engineering

Though the word cognitive has a wide range of meanings we define cognitive engineering as learning from brain to bolster engineering solutions. However, giving an achievable framework to the process towards this has been a difficult task. In this work we take the classic data information knowledge wisdom (DIKW) framework to set some achievable goals and sub-goals towards cognitive engineering. A layered framework like DIKW aligns nicely with the layered structure of pre-frontal cortex. And breaking the task into sub-tasks based on the layers also makes it easier to start developmental endeavours towards achieving the final goal of a brain-inspired system.

cs.AI↗

arXiv2016

Understanding Non-optical Remote-sensed Images: Needs, Challenges and Ways Forward

Non-optical remote-sensed images are going to be used more often in man- aging disaster, crime and precision agriculture. With more small satellites and unmanned air vehicles planning to carry radar and hyperspectral image sensors there is going to be an abundance of such data in the recent future. Understanding these data in real-time will be crucial in attaining some of the important sustain- able development goals. Processing non-optical images is, in many ways, different from that of optical images. Most of the recent advances in the domain of image understanding has been using optical images. In this article we shall explain the needs for image understanding in non-optical domain and the typical challenges. Then we shall describe the existing approaches and how we can move from there to the desired goal of a reliable real-time image understanding system.

cs.CV↗

arXiv2016

A Survey of Brain Inspired Technologies for Engineering

Cognitive engineering is a multi-disciplinary field and hence it is difficult to find a review article consolidating the leading developments in the field. The in-credible pace at which technology is advancing pushes the boundaries of what is achievable in cognitive engineering. There are also differing approaches to cognitive engineering brought about from the multi-disciplinary nature of the field and the vastness of possible applications. Thus research communities require more frequent reviews to keep up to date with the latest trends. In this paper we shall dis-cuss some of the approaches to cognitive engineering holistically to clarify the reasoning behind the different approaches and to highlight their strengths and weaknesses. We shall then show how developments from seemingly disjointed views could be integrated to achieve the same goal of creating cognitive machines. By reviewing the major contributions in the different fields and showing the potential for a combined approach, this work intends to assist the research community in devising more unified methods and techniques for developing cognitive machines.

cs.AI↗

arXiv2016

Application Specific Instrumentation (ASIN): A Bio-inspired Paradigm to Instrumentation using recognition before detection

In this paper we present a new scheme for instrumentation, which has been inspired by the way small mammals sense their environment. We call this scheme Application Specific Instrumentation (ASIN). A conventional instrumentation system focuses on gathering as much information about the scene as possible. This, usually, is a generic system whose data can be used by another system to take a specific action. ASIN fuses these two steps into one. The major merit of the proposed scheme is that it uses low resolution sensors and much less computational overhead to give good performance for a highly specialised application

cs.OH↗

arXiv2015

Design of OFDM radar pulses using genetic algorithm based techniques

The merit of evolutionary algorithms (EA) to solve convex optimization problems is widely acknowledged. In this paper, a genetic algorithm (GA) optimization based waveform design framework is used to improve the features of radar pulses relying on the orthogonal frequency division multiplexing (OFDM) structure. Our optimization techniques focus on finding optimal phase code sequences for the OFDM signal. Several optimality criteria are used since we consider two different radar processing solutions which call either for single or multiple-objective optimizations. When minimization of the so-called peak-to-mean envelope power ratio (PMEPR) single-objective is tackled, we compare our findings with existing methods and emphasize on the merit of our approach. In the scope of the two-objective optimization, we first address PMEPR and peak-to-sidelobe level ratio (PSLR) and show that our approach based on the non-dominated sorting genetic algorithm-II (NSGA-II) provides design solutions with noticeable improvements as opposed to random sets of phase codes. We then look at another case of interest where the objective functions are two measures of the sidelobe level, namely PSLR and the integrated-sidelobe level ratio (ISLR) and propose to modify the NSGA-II to include a constrain on the PMEPR instead. In the last part, we illustrate via a case study how our encoding solution makes it possible to minimize the single objective PMEPR while enabling a target detection enhancement strategy, when the SNR metric would be chosen for the detection framework.

cs.NE↗

arXiv2014

Prefrontal Cortex Motivated Cognitive Architecture for Multiple Robots

In this paper, we introduce a cerebral cortex inspired architecture for robots in which we have mapped hierarchical cortical representation of human brain to logic flow and decision making process. Our work focuses on the two major features of human cognitive process, viz. the perception action cycle and its hierarchical organization, and the decision making process. To prove the effectiveness of our proposed method, we incorporated this architecture in our robot which we named as Cognitive Insect Robot inspired by Brain Architecture (CIRBA). We have extended our research to the implementation of this cognitive architecture of CIRBA in multiple robots and have analyzed the level of cognition attained by them

cs.RO↗

arXiv2014

Optimization of OFDM radar waveforms using genetic algorithms

In this paper, we present our investigations on the use of single objective and multiobjective genetic algorithms based optimisation algorithms to improve the design of OFDM pulses for radar. We discuss these optimization procedures in the scope of a waveform design intended for two different radar processing solutions. Lastly, we show how the encoding solution is suited to permit the optimizations of waveform for OFDM radar related challenges such as enhanced detection.

cs.NE↗

arXiv2014

A Lower Bound for the Variance of Estimators for Nakagami m Distribution

Recently, we have proposed a maximum likelihood iterative algorithm for estimation of the parameters of the Nakagami-m distribution. This technique performs better than state of art estimation techniques for this distribution. This could be of particular use in low data or block based estimation problems. In these scenarios, the estimator should be able to give accurate estimates in the mean square sense with less amounts of data. Also, the estimates should improve with the increase in number of blocks received. In this paper, we see through our simulations, that our proposal is well designed for such requirements. Further, it is well known in the literature that an efficient estimator does not exist for Nakagami-m distribution. In this paper, we derive a theoretical expression for the variance of our proposed estimator. We find that this expression clearly fits the experimental curve for the variance of the proposed estimator. This expression is pretty close to the cramer-rao lower bound(CRLB).

cs.LG↗

arXiv2013

Contraction Principle based Robust Iterative Algorithms for Machine Learning

Iterative algorithms are ubiquitous in the field of data mining. Widely known examples of such algorithms are the least mean square algorithm, backpropagation algorithm of neural networks. Our contribution in this paper is an improvement upon this iterative algorithms in terms of their respective performance metrics and robustness. This improvement is achieved by a new scaling factor which is multiplied to the error term. Our analysis shows that in essence, we are minimizing the corresponding LASSO cost function, which is the reason of its increased robustness. We also give closed form expressions for the number of iterations for convergence and the MSE floor of the original cost function for a minimum targeted value of the L1 norm. As a concluding theme based on the stochastic subgradient algorithm, we give a comparison between the well known Dantzig selector and our algorithm based on contraction principle. By these simulations we attempt to show the optimality of our approach for any widely used parent iterative optimization problem.

cs.LG↗

arXiv2011

Bistatic SAR ATR

With the present revival of interest in bistatic radar systems, research in that area has gained momentum. Given some of the strategic advantages for a bistatic configuration, and tech- nological advances in the past few years, large-scale implementation of the bistatic systems is a scope for the near future. If the bistatic systems are to replace the monostatic systems (at least par- tially), then all the existing usages of a monostatic system should be manageable in a bistatic system. A detailed investigation of the possibilities of an automatic target recognition (ATR) facil- ity in a bistatic radar system is presented. Because of the lack of data, experiments were carried out on simulated data. Still, the results are positive and make a positive case for the introduction of the bistatic configuration. First, it was found that, contrary to the popular expectation that the bistatic ATR performance might be substantially worse than the monostatic ATR performance, the bistatic ATR performed fairly well (though not better than the monostatic ATR). Second, the ATR per- formance does not deteriorate substantially with increasing bistatic angle. Last, the polarimetric data from bistatic scattering were found to have distinct information, contrary to expert opinions. Along with these results, suggestions were also made about how to stabilise the bistatic-ATR per- formance with changing bistatic angle. Finally, a new fast and robust ATR algorithm (developed in the present work) has been presented.

stat.ML↗

arXiv2011

Generation of SAR Image for Real-life Objects using General Purpose EM Simulators

In the applications related to airborne radars, simulation has always played an important role. This is mainly because of the two fold reason of the unavailability of desired data and the difficulty associated with the collection of data under controlled environment. A simple example will be regarding the collection of pure multipolar radar data. Even after phenomenal development in the field of radar hardware design and signal processing, till now the collection of pure multipolar data is a challenge for the radar system designers. Till very recently, the power of computer simulation of radar signal return was available to a very selected few. This was because of the heavy cost associated with some of the main line electro magnetic (EM) simulators for radar signal simulation, and secondly because many such EM simulators are for restricted marketting. However, because of the fast progress made in the field of EM simulation, many of the current generic EM simulators can be used to simulate radar returns from realistic targets. The current article expounds the steps towards generating a synthetic aperture radar (SAR) image database of ground targets, using a eneric EM g simulator. It also demonstrates by the help of some example images, the quality of the SAR mage generated i using a general purpose EM simulator.

stat.ML↗

arXiv2011

Fast and Modular Analog Rank Order Filter Using CMOS Technology

In this paper, we apply the sorting network theory to construct an analog rank order filter. We present a voltage mode CMOS two-input sorting element and arrange these to form a rank order filter. The resulting circuit is simpleand is a high-speed, high-precision design. Although the transistor count is moderately higher than other designs, the proposed circuit simultaneously outputs signals of all ranks rather than of just one specified rank. We also develop a slightly modified design which calculates the rank of a given signal. We present reports of simulations to verify the performance of the device.

physics.ins-det↗