State Amplification

We consider the problem of transmitting data at rate R over a state dependent channel p(y|x,s) with the state information available at the sender and at the same time conveying the information about the channel state itself to the receiver. The amount of state information that can be learned at the receiver is captured by the mutual information I(S^n; Y^n) between the state sequence S^n and the channel output Y^n. The optimal tradeoff is characterized between the information transmission rate R and the state uncertainty reduction rate \Delta, when the state information is either causally or noncausally available at the sender. This result is closely related and in a sense dual to a recent study by Merhav and Shamai, which solves the problem of masking the state information from the receiver rather than conveying it.Comment: 9 pages, 4 figures, submitted to IEEE Trans. Inform. Theory, revise

Linear Algebra

In order not to intimidate students by a too abstract approach, this textbook on linear algebra is written to be easy to digest by non-mathematicians. It is also designed such that no other material is required for an understanding of the topics covered. As the basis for courses on space and atmospheric science, remote sensing, and satellite communications, applications of the formal theory in physics and engineering are discussed as well

Probability and Statistics

This textbook offers an introduction to concepts of probability theory, probability distributions relevant in the applied sciences, as well as basics of sampling distributions, estimation and hypothesis testing. As a companion for classes for engineers and scientists, the book also covers applied topics such as model building and experiment design

Linear Algebra

In order not to intimidate students by a too abstract approach, this textbook on linear algebra is written to be easy to digest by non-mathematicians. It is also designed such that no other material is required for an understanding of the topics covered. As the basis for courses on space and atmospheric science, remote sensing, and satellite communications, applications of the formal theory in physics and engineering are discussed as well

Probability and Statistics

This textbook offers an introduction to concepts of probability theory, probability distributions relevant in the applied sciences, as well as basics of sampling distributions, estimation and hypothesis testing. As a companion for classes for engineers and scientists, the book also covers applied topics such as model building and experiment design

Multivariate Statistical Analysis in the Real and Complex Domains

This book explores topics in multivariate statistical analysis, relevant in the real and complex domains. It utilizes simplified and unified notations to render the complex subject matter both accessible and enjoyable, drawing from clear exposition and numerous illustrative examples. The book features an in-depth treatment of theory with a fair balance of applied coverage, and a classroom lecture style so that the learning process feels organic. It also contains original results, with the goal of driving research conversations forward. This will be particularly useful for researchers working in machine learning, biomedical signal processing, and other fields that increasingly rely on complex random variables to model complex-valued data. It can also be used in advanced courses on multivariate analysis. Numerous exercises are included throughout

Multivariate Statistical Analysis in the Real and Complex Domains

This book explores topics in multivariate statistical analysis, relevant in the real and complex domains. It utilizes simplified and unified notations to render the complex subject matter both accessible and enjoyable, drawing from clear exposition and numerous illustrative examples. The book features an in-depth treatment of theory with a fair balance of applied coverage, and a classroom lecture style so that the learning process feels organic. It also contains original results, with the goal of driving research conversations forward. This will be particularly useful for researchers working in machine learning, biomedical signal processing, and other fields that increasingly rely on complex random variables to model complex-valued data. It can also be used in advanced courses on multivariate analysis. Numerous exercises are included throughout

Experimental study of the distribution of the heights of sugar beet root crowns above the soil surface

ArticleThe results of experimental studies and operational tests of the sugar beet harvesting process carried out recently reveal that the latest models of beet harvesters produced in Europe and America cause considerable loss of the sugar-bearing mass. The source of this loss is mainly the poor topping of the crowns of standing sugar beet roots, more specifically the excessively low point at which the tops are cut off, which results in the straight out loss of sugar-bearing mass. Thus, there is need to search for such engineering solutions that would avoid both the loss of sugar-bearing mass and the presence of residual haulm on the roots. The aim of this study was to reduce the loss of sugar-bearing mass in the process of topping sugar beet root crowns. The results of this research into the distribution of the heights that root crowns protrude above the soil surface have confirmed the hypothesis that it follows the normal distribution. Based on the results, it has been established that this distribution has the following statistical parameters: mean deviation a = 20–30 mm, mathematical expectation m = 40...60 mm. The laboratory unit developed for this work and the field studies performed with it have provided sufficient evidence to develop a new system to automatically adjust the topping height on state-of-the-art root crop harvesters

Research into properties of blue melilot and fenugreek cultivated using different sowing times

Received: September 6th, 2021 ; Accepted: January 30th, 2022 ; Published: February 17th, 2022 ; Correspondence: [email protected] paper presents the results of the research into the properties of blue melilot (Melilotus caeruleus (L.) Desr.) and fenugreek (Trigonella foenum graecum L.) with regard to the set of their economy-and-biology and biochemical indices in relation to the dates of their sowing. It has been established that the two species under consideration feature wide ranges of index variability depending on the sowing term and the weather conditions. The earliest ripening terms have been recorded for species in case of summer sowing dates (decade I of June), when short growing season lengths of 36–37 days were observed. At the same time, in terms of heavy plant herbage yield obtained from species in the green conveyor system, the early spring (decades II–III of April) and late spring (decade I of May) sowing terms are more suitable providing a herbage yield of 5.7–6.9 t ha–1 in case of blue melilot and 7.3–9.3 t ha–1 for fenugreek, with a solids content of 12.4–28.4%, total sugars of 2.5–5.0% and vitamin C - 38.0–51.8 mg (100 g)-1 . For the purpose of obtaining the spice named ‘Greek hay’ (foenum Graecum), a better choice is to cultivate fenugreek with early spring (decades II–III of April) and late spring (decade I of May) sowing times, as in this case a greater vegetation mass develops, resulting in a plant dry weight yield of 1.3–1.4 t ha–1. An increase in the total precipitation by 1 mm has contributed to the variation of the herbage yield within the range of 15.0 to 77.3 kg ha–1, dry matter yield - 0.693 to 25.9 kg ha–1. High seed yield has been noted in case of sowing the species in early spring (decades II–III of April), where the seed yield of blue melilot was equal to 0.4 t ha-1, fenugreek - 2.0 t ha-1 , their 1,000 seeds having a weight of 0.71 and 9.7 g, respectively