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Courseware
This course introduces architecture of digital systems, emphasizing structural principles common to a wide range of technologies. It covers the topics including multilevel implementation strategies, definition of new primitives (e.g., gates, instructions, procedures, processes) and their mechanization using lower-level elements. It also includes analysis of potential concurrency, precedence constraints and performance measures, pipelined and multidimensional systems, instruction set design issues and architectural support for contemporary software structures.
- Subjects:
- Computing, Data Science and Artificial Intelligence and Electrical Engineering
- Keywords:
- Digital electronics
- Resource Type:
- Courseware
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Courseware
This course covers signals, systems and inference in communication, control and signal processing. Topics include input-output and state-space models of linear systems driven by deterministic and random signals; time- and transform-domain representations in discrete and continuous time; and group delay. State feedback and observers. Probabilistic models; stochastic processes, correlation functions, power spectra, spectral factorization. Least-mean square error estimation; Wiener filtering. Hypothesis testing; detection; matched filters.
- Subjects:
- Electronic and Information Engineering and Electrical Engineering
- Keywords:
- Signal theory (Telecommunication) Signal processing System analysis
- Resource Type:
- Courseware
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Courseware
This course introduces the foundations of database systems, focusing on basics such as the relational algebra and data model, schema normalization, query optimization, and transactions. It is designed for students who have taken 6.033 (or equivalent); no prior database experience is assumed, though students who have taken an undergraduate course in databases are encouraged to attend.
- Subjects:
- Computing, Data Science and Artificial Intelligence
- Keywords:
- Database management
- Resource Type:
- Courseware
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Video
In this video we look at how to decide for a given scenario (worded problem) if the distribution described is a Binomial distribution or Poisson distribution and whether its probability distribution function or its cumulative distribution function is required to calculate a specified probability.
- Subjects:
- Mathematics and Statistics
- Keywords:
- Probabilities Poisson distribution Distribution (Probability theory) Binomial distribution
- Resource Type:
- Video
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Video
In this video we look at how to use statistical tables to calculate probabilities in a Binomial distribution. This includes an example of using the table for the probability density function to determine the probability the random variable takes a particular value and an example of using the table for the cumulative distribution function to determine the probability the random variable is less than or equal to a certain value and an example determining the probability it is greater than or equal to a certain value.
- Subjects:
- Mathematics and Statistics
- Keywords:
- Probabilities Poisson distribution Distribution (Probability theory)
- Resource Type:
- Video
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Video
In this video we look at how to use statistical tables to calculate probabilities in a Poisson distribution. This includes an example of using the table for the probability density function to determine the probability the random variable is equal to particular value in a case where the average number of events per interval needs to be adjusted to match the units specified in the question and an example of using the table for the cumulative distribution function to determine the probability the random variable takes a value between two specified numbers.
- Subjects:
- Mathematics and Statistics
- Keywords:
- Probabilities Distribution (Probability theory) Binomial distribution
- Resource Type:
- Video
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Video
In this video we look at how to use statistical tables to calculate probabilities in a Poisson distribution. This includes an example of using the table for the probability density function to determine the probability the random variable is equal to a particular value and an example of using the table for the cumulative distribution function to determine the probability the random variable is less than a certain value and an example determining the probability it is greater than or equal to a certain value.
- Subjects:
- Mathematics and Statistics
- Keywords:
- Probabilities Poisson distribution Distribution (Probability theory)
- Resource Type:
- Video
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e-book
Pattern recognition, despite its relatively short history, has already found practical application in many areas of human activity. Systems of pattern recognition usually support people in performing tasks related to ensuring security, including access to premises and devices, detection of unusual changes (e.g. in medicine, cartography, geology), diagnosing technical conditions of devices, and many others. Nevertheless, pattern recognition is probably the most developing area because of the great demand for such solutions in the different areas of our lives. In this book we have collected the experience of scientists from different parts of the world who have researched diverse areas connected directly or indirectly with pattern recognition. We hope that this book will be a treasure trove of knowledge and inspiration for further research in the field of pattern recognition.
- Subjects:
- Computing, Data Science and Artificial Intelligence and Electronic and Information Engineering
- Keywords:
- Pattern perception Image processing Pattern recognition systems
- Resource Type:
- e-book
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e-book
The book focuses on the creation, manipulation, transmission, and reception of information by electronic means. Elementary signal theory; time- and frequency-domain analysis; Sampling Theorem. Digital information theory; digital transmission of analog signals; error-correcting codes.
- Subjects:
- Electrical Engineering
- Keywords:
- Electrical engineering
- Resource Type:
- e-book
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Others
The data presented in this article are related to the research article entitled: “Information Strategies for Energy Conservation: A Field Experiment in India” (Victor L. Chen, Magali A. Delmas, Stephen L. Locke, Amarjeet Singh, 2017).The availability of high-resolution electricity data offers benefits to both utilities and consumers to understand the dynamics of energy consumption for example, between billing periods or times of peak demand. However, few public datasets with high-temporal resolution have been available to researchers on electricity use, especially at the appliance-level. In this article, we describe data collected in a residential field experiment for 19 apartments at an Indian faculty housing complex during the period from August 1, 2013 to May 12, 2014. The dataset includes detailed information about electricity consumption. It also includes information on apartment characteristics and hourly weather variation to enable further studies of energy performance. These data can be used by researchers as training datasets to evaluate electricity usage consumption.
- Subjects:
- Electrical Engineering
- Keywords:
- India Electric power -- Conservation Electric power consumption
- Resource Type:
- Others