Timo Hämäläinen

Bio: Timo Hämäläinen is an academic researcher from University of Jyväskylä. The author has contributed to research in topics: Quality of service & Encoder. The author has an hindex of 38, co-authored 560 publications receiving 7648 citations. Previous affiliations of Timo Hämäläinen include Dalian Medical University & Nokia.

Enhanced admission control solution for multicasting with DiffServ

Abstract: Multicast admission control in differentiated services network is an important but shortly researched subject. We propose a parameter-based admission control method. The method rejects new multicast join requests that would otherwise decrease the quality experienced by the existing receivers. DiffServ network edge nodes filter join requests and generate new requests. The proposed method is developed as an extension to the DSMCast protocol but could also be adapted to other protocols. In this paper the parameter-based admission control is compared to earlier created, measurement-based admission control methods, as well to situation when no admission control is used.

Inverse Scattering Solutions with Applications to Electromagnetic Signal Processing

Abstract: When a signal is recorded that has been physi- cally generated by some scattering process (the interaction of electromagnetic, acoustic or elastic waves with inhomogeneous materials, for example), the 'standard model' for the signal (i.e. information content convolved with a characteristic Impulse Response Function) is usually based on a single scattering approximation. An additive noise term is introduced into the model to take into account a range of non-deterministic factors including multiple scattering that, along with electronic noise and other background noise sources, is assumed to be relatively weak. Thus, the standard model is based on a 'weak field condition' and the inverse scattering problem is often reduced to the deconvolution of a signal in the presence of additive noise. Attempts at solving the exact inverse scattering problem for equations such as the inhomogeneous Schr¨ odinger equation in quantum mechanics and the inhomogeneous Helmholtz equation in electromagnetism often prove to be intractable, particularly with regard to the goal of implementing algorithms that are computationally stable and/or compatible with standard signal analysis methods and Digital Signal Processing 'toolkits'. This paper provides an approach to solving the multiple scattering problem for narrow side-band systems (typically, electromagnetic signal processing systems) that is compounded in the introduction of a single extra term to the standard model. The approach is based on applying certain conditions to an exact solution of the inverse scattering problem rather than applying conditions to the forward scattering problem and then inverting the (conditional) result.

The simulation and analysis of the revenue critierion based adaptive WFQ

Abstract: This paper presents the simulation and analysis of the adaptive resource allocation model, which was proposed and theoretically considered in our previous works. It relies upon the Weighted Fair Queueing (WFQ) service policy and uses the revenue criterion to adjust weights. The purpose of the proposed model is to maximize a provider's revenue and, at the same time, ensure the required Quality-of-Service (QoS) for end-users. Our previous works provided the theoretical evaluation of the proposed model and considered the single-node case only. This paper presents more realistic network scenario, which includes a set of clients and several intermediate switching nodes with the proposed model. The adaptive and non-adaptive approaches to the WFQ are considered in terms of obtained revenue and state of queues at intermediate nodes. It is shown that the adaptive approach can improve the total revenue obtained by a provider when compared to the non-adaptive approach.

Bridging network traffic between wireless and wired lans in Windows NT

Abstract: This paper presents two different alternatives for interconnecting Local Area Networks (LANs) in the data link layer. The solutions use a Windows NT workstation as a bridge between separate networks. Interconnection is provided by either implementing an intermediate driver or a protocol driver into the Windows NT networking stack. Both alternatives screen traffic according to the address fields of network frames and therefore unnecessary traffic can be avoided. Bridge will be used for interconnections between an Ethernet wired LAN, a standard IEEE 802.11 wireless LAN, and TUTWLAN that is a wireless LAN designed at Tampere University of Technology. The protocol driver is concluded to be a more practical alternative for implementing the bridging functionality in TUTWLAN because of its simpler structure and estimated higher performance.

Registration performance comparison between IP Multimedia Subsystem and Session Initiation Protocol networks

Abstract: The IP Multimedia Subsystem (IMS) is an IP based service control framework architecture. It uses Session Initiation Protocol (SIP) to control its multimedia sessions. The IMS core can be considered as a collection of different functions that are linked with standard interfaces, forming an IMS core network. The IMS has layers for transport, the core itself, and for services and applications. The complexity of the IMS core is greater than within pure SIP based networks. To help to make comparisons between different IMS networks, the ETSI-TISPAN has unified the IMS performance measurements by defining a common framework which to follow. In this paper, the Open IMS solution by the Fraunhover Focus Institute is compared with the OpenSIPS, an open source SIP server used for user's registrations to network. The number of users was chosen to be 100 000, a large enough number to be considered as a suitable number of users for small or moderate business usage needs. Our study shows that both of the systems are able to handle this many users and, in the case of OpenSIPS, with a clear margin. It was also discovered that both systems are reliable and are suitable for small and moderate business usage and further performance study trials

I and i

Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

Machine learning

Abstract: Machine Learning is the study of methods for programming computers to learn. Computers are applied to a wide range of tasks, and for most of these it is relatively easy for programmers to design and implement the necessary software. However, there are many tasks for which this is difficult or impossible. These can be divided into four general categories. First, there are problems for which there exist no human experts. For example, in modern automated manufacturing facilities, there is a need to predict machine failures before they occur by analyzing sensor readings. Because the machines are new, there are no human experts who can be interviewed by a programmer to provide the knowledge necessary to build a computer system. A machine learning system can study recorded data and subsequent machine failures and learn prediction rules. Second, there are problems where human experts exist, but where they are unable to explain their expertise. This is the case in many perceptual tasks, such as speech recognition, hand-writing recognition, and natural language understanding. Virtually all humans exhibit expert-level abilities on these tasks, but none of them can describe the detailed steps that they follow as they perform them. Fortunately, humans can provide machines with examples of the inputs and correct outputs for these tasks, so machine learning algorithms can learn to map the inputs to the outputs. Third, there are problems where phenomena are changing rapidly. In finance, for example, people would like to predict the future behavior of the stock market, of consumer purchases, or of exchange rates. These behaviors change frequently, so that even if a programmer could construct a good predictive computer program, it would need to be rewritten frequently. A learning program can relieve the programmer of this burden by constantly modifying and tuning a set of learned prediction rules. Fourth, there are applications that need to be customized for each computer user separately. Consider, for example, a program to filter unwanted electronic mail messages. Different users will need different filters. It is unreasonable to expect each user to program his or her own rules, and it is infeasible to provide every user with a software engineer to keep the rules up-to-date. A machine learning system can learn which mail messages the user rejects and maintain the filtering rules automatically. Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis. Statistics focuses on understanding the phenomena that have generated the data, often with the goal of testing different hypotheses about those phenomena. Data mining seeks to find patterns in the data that are understandable by people. Psychological studies of human learning aspire to understand the mechanisms underlying the various learning behaviors exhibited by people (concept learning, skill acquisition, strategy change, etc.).

Survey of Wireless Indoor Positioning Techniques and Systems

Abstract: Wireless indoor positioning systems have become very popular in recent years. These systems have been successfully used in many applications such as asset tracking and inventory management. This paper provides an overview of the existing wireless indoor positioning solutions and attempts to classify different techniques and systems. Three typical location estimation schemes of triangulation, scene analysis, and proximity are analyzed. We also discuss location fingerprinting in detail since it is used in most current system or solutions. We then examine a set of properties by which location systems are evaluated, and apply this evaluation method to survey a number of existing systems. Comprehensive performance comparisons including accuracy, precision, complexity, scalability, robustness, and cost are presented.

The Self-Organizing Map

Abstract: An overview of the self-organizing map algorithm, on which the papers in this issue are based, is presented in this article.