An approach for calculating electromagnetic scattering, valid in the near- and far-field regions, from a homogeneous finite cylindrical vegetation sample at oblique incidence is presented and discussed. The proposed solution will help in taking into account multiple scattering effects due to plant structure. It does not require assumptions on the dimensions or electromagnetic properties of the vegetation cylinder.

The advancement in wireless communications requires the integration of multiple radios into a single platform to maximize connectivity. In this paper, the design process of reconfigurable antennas is discussed. Reconfigurable antennas are proposed to cover different wireless services that operate over a wide frequency range. They show significant promise in addressing new system requirements. They exhibit the ability to modify their geometries and behavior to adapt to changes in surrounding conditions. Reconfigurable antennas can deliver the same throughput as a multiantenna system. They use dynamically variable and adaptable single-antenna geometry without increasing the real estate required to accommodate multiple antennas. The optimization of reconfigurable antenna design and operation by removing unnecessary redundant switches to alleviate biasing issues and improve the system's performance is discussed. Controlling the antenna reconfiguration by software, using Field Programmable Gate Arrays (FPGAs) or microcontrollers is introduced herein. The use of Neural Networks and its integration with graph models on programmable platforms and its effect on the operation of reconfigurable antennas is presented. Finally, the applications of reconfigurable antennas for cognitive radio, Multiple Input Multiple Output (MIMO) channels, and space applications are highlighted.

The articles in this special issues are the first of two special issues that will provide an in-depth treatment of the subject of reconfigurable systems as enabled through advancements in the electrical engineering field, as well as the approaches we use to manage complexity in systems having millions of fixed and programmable elements. It is our view that the frenetic evolution of the field programmable gate array (FPGA) as a preeminent digital platform will not only continue for the foreseeable future, but will serve as an inspiration/template for other functional domains to include analog, radio-frequency, photonic, and even those not strictly electrical in nature to include thermal, fluidic, and mechanical. This issue will serve as an immersion into the subject of reconfigurable systems, both for the purposes of gaining familiarity with essential theoretical elements, the key developments in the field, and the potential future directions.

Reconfigurability can be thought of as software-defined functionality, where flexibility is controlled predominately through the specification of bit patterns. Reconfigurable systems can be as simple as a single switch, or as abstract and powerful as programmable matter. This paper considers the generalization of reconfigurable systems as an important evolving discipline, bolstered by real-world archetypes such as field programmable gate arrays and software-definable radio (platform and application, respectively). It considers what reconfigurable systems actually are, their motivation, their taxonomy, the fundamental mechanisms and architectural considerations underlying them, designing them and using them in applications. With well-known real-world instances, such as the field programmable gate array, the paper attempts to motivate an understanding of the many possible directions and implications of a new class of system which is fundamentally based on the ability to change.

The articles in this special issue focus on reconfigurable systems. Reconfigurability is about "change," specifically soft-defined change, whereby through the manipulation of bit sequences we can customize the properties of components, and in some cases define systems themselves. One can design systems for reconfigurability (the art of engineering degrees of freedom into embedded systems), so that users expecting this reconfigurability can exploit it. This issue focuses on important reconfigurable platforms [field-programmable gate arrays (FPGAs)], development tools, and applications (reconfigurable computing and software radios). As we discussed, reconfigurability can be both dynamic and adaptive, but one should not confuse the two concepts. Reconfigurability refers to specific features that can be changed (to include dynamic and partial reconfigurability), whereas adaptiveness addresses the behavioral constructs that inform how reconfigurable features might best be exploited in live use conditions.

A new solution to estimate multiple scattering from two cylinders is presented. It is based on both cylindrical and plane wave expansions, the known scattering from infinite cylinders and the far-field scattering from lossy dielectric finite cylinders. The solution is used in calculating multiple scattering from two finite length cylinders with different orientations for the general case of oblique incidence. It is assumed that the length of the cylinder is large compared to its diameter which is a good approximation for most tree trunks and branches.

Reconfigurable antennas, with the ability to radiate more than one pattern at different frequencies and polarizations, are necessary in modern telecommunication systems. The requirements for increased functionality (e.g., direction finding, beam steering, radar, control, and command) within a confined volume place a greater burden on today's transmitting and receiving systems. Reconfigurable antennas are a solution to this problem. This paper discusses the different reconfigurable components that can be used in an antenna to modify its structure and function. These reconfiguration techniques are either based on the integration of radio-frequency microelectromechanical systems (RF-MEMS), PIN diodes, varactors, photoconductive elements, or on the physical alteration of the antenna radiating structure, or on the use of smart materials such as ferrites and liquid crystals. Various activation mechanisms that can be used in each different reconfigurable implementation to achieve optimum performance are presented and discussed. Several examples of reconfigurable antennas for both terrestrial and space applications are highlighted, such as cognitive radio, multiple-input–multiple-output (MIMO) systems, and satellite communication.

Pulsed power is a technology that is suited to drive electrical loads requiring very large power pulses in short bursts (high-peak power). Certain applications require technology that can be deployed in small spaces under stressful environments, e.g., on a ship, vehicle, or aircraft. In 2001, the U.S. Department of Defense (DoD) launched a long-range (five-year) Multidisciplinary University Research Initiative (MURI) to study fundamental issues for compact pulsed power. This research program is endeavoring to: 1) introduce new materials for use in pulsed power systems; 2) examine alternative topologies for compact pulse generation; 3) study pulsed power switches, including pseudospark switches; and 4) investigate the basic physics related to the generation of pulsed power, such as the behavior of liquid dielectrics under intense electric field conditions. Furthermore, the integration of all of these building blocks is impacted by system architecture (how things are put together). This paper reviews the advances put forth to date by the researchers in this program and will assess the potential impact for future development of compact pulsed power systems.

The paper presents a multiclass, multilabel implementation of least squares support vector machines (LS-SVM) for direction of arrival (DOA) estimation in a CDMA system. For any estimation or classification system, the algorithm's capabilities and performance must be evaluated. Specifically, for classification algorithms, a high confidence level must exist along with a technique to tag misclassifications automatically. The presented learning algorithm includes error control and validation steps for generating statistics on the multiclass evaluation path and the signal subspace dimension. The error statistics provide a confidence level for the classification accuracy.