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A large number of real networks are characterized by two fundamental properties: they are small world and scale-free. A recent paper demonstrated that the structure of many complex networks is also self-similar under a length-scale transformation, and calculated their fractal dimension using the "box counting" method. We studied nine large object-oriented software systems, finding that the graphs associated to these networks are self-similar. We also studied the time evolution of the fractal dimension during system growth, finding a significant correlation between the fractal dimension and object-oriented complexity metrics known to be correlated with software fault-proneness. Thus, in software systems the fractal dimension could be considered as a measure of internal complexity, and consequently of the system quality.

We present a study of three large object-oriented software systems—VisualWorks Smalltalk, Java JDK and Eclipse—searching for scaling laws in some of their properties. We study four system properties related to code production, namely the inheritance hierarchies, the naming of variables and methods, and the calls to methods. We systematically found power-law distributions in these properties, most of which have never been reported before. We were also able to statistically model the programming activities leading to the studied properties as Yule processes, with very good correspondence between empirical data and the prediction of Yule model. The fact that a design and optimization process like software development can be modeled on the large with the laws of statistical physics poses intriguing issues to software engineers, and could be exploited for finding new metrics and quality measures.

In this paper, we study the long-run wealth distribution of agents with different trading strategies in the framework of the Genoa Artificial Stock Market. The Genoa market is an agent-based simulated market able to reproduce the main stylised facts observed in financial markets, i.e., fat-tailed distribution of returns and volatility clustering. Various populations of traders have been introduced in a 'thermal bath' made by random traders who make random buy and sell decisions constrained by the available limited resources and depending on past price volatility. We study both trend following and trend contrarian behaviour; fundamentalist traders (i.e., traders believing that stocks have a fundamental price depending on factors external to the market) are also investigated. Results show that the strategy alone does not allow forecasting which population will prevail. Trading strategies yield different results in different market conditions. Generally, in a closed market (a market with no money creation process), we find that trend followers lose relevance and money to other populations of traders and eventually disappear, whereas in an open market (a market with money inflows), trend followers can survive, but their strategy is less profitable than the strategy of other populations.

The aim of this paper is to present a dataset of metrics as- sociated to the first release of a curated collection of Python software systems. We describe the dataset along with the adopted criteria and the issues we faced while building such corpus. This dataset can enhance the reliability of empirical studies, enabling their reproducibility, reducing their cost, and it can foster further research on Python software.

Refactoring is certainly one of the most widespread practices used by developers to improve software quality. During the last two decades, it has been the subject of an increasing number of research studies. But how much do we know about the trends, and the appearance of new topics, in the research field of refactoring? What have researchers found about its application since the time of its first introduction? In this work we provide a preliminary analysis of the state of the art and the evolution of the research on refactoring. We attempt to represent the actual body of knowledge in this field through the analysis of its cognitive structure, leveraging science mapping methodology to focus on the most relevant concepts in this research area. We model the body of knowledge by mining bibliographic databases and by retrieving the co-occurrence of keywords. We have found that some different general themes can be recognized, but not all of them have the same role and equally catalyzed researchers' interest. In addition, we provide a preliminary analysis on the trends and directions as well as the hot topics we identified in the refactoring research field.

This paper presents a model of stock price behavior that encompasses both short-term fluctuations and long-term exponential trends punctuated by crashes. The model represents stock market behavior as the interaction of two self-organizing processes. The first process represents business-as-usual stock price fluctuations. It builds on a model of stock price behavior introduced by Cont and Bouchaud. The second process is a risk process that determines the severity of crashes. It is a random graph process driven by macroeconomic variables. Our model is based on the assumption that stock market prices that grow at a higher rate than the real economy force structural changes that, in turn, leverage the risk of a crash. The transition from a business-as-usual regime to a crash regime is determined by trigger events. Trigger events are exponentially distributed while the size of a crash depends on the state of the underlying risk process. While in the short-term the performance of stock prices may be determined by the purely speculative behavior of agents, the long-term behavior of stock prices is essentially a function of structural and macroeconomic parameters.

We present a stochastic simulation model of a prototype financial market. Our market is populated by both noise traders and fundamentalist speculators. The dynamics covers switches in the prevailing mood among noise traders (optimistic or pessimistic) as well as switches of agents between the noise trader and fundamentalist group in response to observed differences in profits. The particular behavioral variant adopted by an agent also determines his decision to enter on the long or short side of the market. Short-run imbalances between demand and supply lead to price adjustments by a market maker or auctioneer in the usual Walrasian manner. Our interest in this paper is in exploring the behavior of the model when testing for the presence of chaos or non-linearity in the simulated data. As it turns out, attempts to determine the fractal dimension of the underlying process give unsatisfactory results in that we experience a lack of convergence of the estimate. Explicit tests for non-linearity and dependence (the BDS and Kaplan tests) also give very unstable results in that both acceptance and strong rejection of IIDness can be found in different realizations of our model. All in all, this behavior is very similar to experience collected with empirical data and our results may point towards an explanation of why robustness of inference in this area is low. However, when testing for dependence in second moments and estimating GARCH models, the results appear much more robust and the chosen GARCH specification closely resembles the typical outcome of empirical studies.

Since "design-oriented" life-cycles came to their maturity, dramatic changes have been introduced as far as programming tools and computer hardware are concerned. Such changes made it possible to develop applications focusing on refactoring rather than on analysis and design. The underlying hypothesis is that by adopting suitable tools and target languages, refactoring would possibly cost less than the overhead introduced by modern A&D techniques. Recently, extreme programming has been proposed as an alternative to a "design-oriented" life-cycle.In this paper we describe a software application developed using a software life-cycle that basically follows the guidelines suggested by extreme programming. Such an approach requires highly expressive programming languages and powerful CASE tools. UML has been selected as the underlying modeling language throughout the whole process, for it incorporates well-known diagrams for describing a software application from different perspectives. Smalltalk has been selected as target language, as it allows fast prototyping and early delivery. We claim that, for small and medium-sized projects, a life-cycle based on refactoring and supported by suitable languages and tools allows team productivity to be greatly enhanced.

This paper presents a tabu search based strategy which is applied to optimize the objective function associated with the design of a solenoid system. The strategies used to apply tabu search in a continuous domain are developed without increasing computational effort with respect to the corresponding discrete problem. Algorithms developed for discrete problems used to self-tune tabu search parameters have also been applied, achieving improvements in terms of the quality of the solutions.

A numerically efficient model of nonlinear electromagnetic devices under different supply modes is presented. The model is based on feedforward neural networks (NNs) properly inputted for voltage and current supply. The NN model allows a close prediction of typical hysteretic behavior of these devices. Comparisons with other models (e.g. Chua-Stromsmoe and Jiles-Atherton) and experimental data are also reported.

This paper presents a neural network system for the diagnosis of analog circuits and shows how the performance of such a system can be affected by the choice of different techniques used by its submodules. In particular we discuss the influence of feature extraction techniques such as Fourier Transforms, Wavelets and Principal Component Analysis. The system uses several different power supplies and as many neural networks “in parallel”. Two different algorithms that can be used to combine the candidate sets produced by each network are also presented. The system is capable of diagnosing multiple faults even if trained on single ones.

To maintain a good voltage quality level to customers in power distribution system, it is essential to minimise transients, line voltage dips and spikes due to a variety of causes, including fault occurrence, power interruption and large load changes. In case of private generating systems it is essential that ultra-rapid switching devices be used which cut off the customer plant from the utility system so quickly that the presence of voltage dips is not perceived by the industrial plant's sensitive loads. These devices require very fast acquisition and control systems which permit to diagnose and, possibly, predict abnormal events. In this paper, a control methodology based on a locally recurrent-globally feed-forward neural network and on a neural classifier is proposed. It will be shown that it is possible to predict with good accuracy the value of the control variables based on previously acquired samples and use these values to recognise the kind of abnormal event that is about to occur on the network.

The finding of clustered volatility and ARCH effects is ubiquitous in financial data. This paper presents a possible explanation of this phenomenon within a multi-agent framework of speculative activity. In the model, both chartist and fundamentalist strategies are considered with agents switching between both behavioural variants according to observed differences in pay-offs. Price changes are brought about by a market maker reacting on imbalances between demand and supply. Most of the time, a stable and efficient market results. However, its usual tranquil performance is interspersed by sudden transient phases of destabilisation. Outbreak of volatility occurs if the fraction of agents using chartist techniques surpasses a certain threshold value, but such phases are quickly brought to an end by stabilising tendencies. Formally, this pattern can be understood as an example of a new type of dynamic behaviour denoted on-off intermittency in physics literature. Statistical analysis of simulated time series shows that the main stylised facts (unit roots in levels together with heteroscedasticity and leptokurtosis of returns) can be found in this “artificial” market

This paper presents a Tabu Search based strategy which has been applied to optimize the objective function associated to the design of a solenoids system. For this kind of problem, Tabu Search strategies are able to find the global minimum with considerably better performance than that obtained using a Simulated Annealing algorithm. Algorithms used to perform the self-tuning of Tabu Search parameters have also been developed, achieving interesting improvements in terms of computing time and quality of the solutions. Such algorithms are an original development of Reactive Tabu Search and they are based on the past history of the search. Tabu Search strategies have also been applied in continuous optimization of the same problem with encouraging results.

This paper presents a 2D hysteresis model constructed to represent the magnetic behavior of steel laminates. A superposition of three simplified models (two scalar models and one vectorial) was considered. The obtained results show that the model is sufficiently accurate to represent the material hysteresis losses and simple enough to be used in finite element method calculations.

In recent years, the power balance between software firms and enterprise customers has been heavily changing. The contractual power of customers is increasing and the firms must take this fact into account. Stated the common need to save money, the opportunities to adopt new software solutions with tight budgets, or with substantial savings, are limited. The better way to obtain operational savings seems to be shifting to the use of open source software, obtaining in this way all the benefits of this software typology: lower costs, greater adherence to open standards, a broader vendor choice and service suppliers, no vendor lock-in and flexible, incremental architectures. In this work, a business model is proposed to analyse the competition among on-demand customer relationship management (CRM) firms, in particular among firms offering CRM products with or without source code availability. The model can also be customized to study other kinds of markets, and other assumptions can be made for study...

Agile software development is now in its teens. It began by performing in relatively small pioneering organizations; then it gained the interest of medium-size companies, academia, and applied research institutions and laboratories; nowadays it runs in organizations of any kind, including major software and systems development companies. Because of such a wide diffusion of Agile in industry, the need for collaboration between academics and practitioners increases, in the aim of improving the body of knowledge available to help managers, system engineers, and software engineers to take their managerial/economical, and architectural/project / technical decisions. During its 15 editions, the XP conference has been a major supporter of the Agile vision of software development. Year after year, the XP conference has been supporting the improvements, observing the growth, of the Agile software development and providing evidence about the advantages that Agile development can provide. In fact, these XP editions brought together industrial practitioners and researchers in the fields of information systems and software development. They examined latest theory, practical applications and implications of agile and lean methods. XP2014, in continuity with the past editions, built a multidisciplinary platform for research and practice on various aspects of agile methods, increased interaction and collaboration between practitioners and researchers, discussed and rethought the relationships, synergies, compatibilities and incompatibilities between agile and lean practices. XP2014 committees included the Research Program Committee and the Experience Report Program Committee. This book presents the regular papers and short papers that the former, and the experience reports that the latter, respectively, accepted for presentation at XP2014. Let’s note that the acceptance process was really selective; specifically, more than 50% of the submitted papers and experience reports were rejected. This book presents chapters concerning or rethinking Agile and Lean development research topics, including: Contracting, Maturity modeling, Value-Based Software Development, Large-Scale Software Development, Methods, Metrics, Testing, Challenges and Perspectives, Software Development in Practice and Teaching at University. The experience reports come from both industry and research institutes, and their topics span from studying global architecture design approaches to investigating challenges involved when advancing software development practices. Hopefully, we reached the goal of doing our best in serving the Agile community by synthesizing the states of the art and practice and tracing its perspectives.

A greedy genetic algorithm for continuous variables electromagnetic optimization problems is presented. The presented algorithm is characterized by the use of a nonlinear simplex method as a principal optimizer, and of a greedy genetic algorithm to explore the search space, realizing a balance between diversity and a bias toward fitter individuals. The resulting algorithm merges the efficiency typical of calculus-based search with the robustness typical of random methods. A detailed comparison of the performance obtained implementing several strategies is presented, using an electromagnetic design test problem.

Welcome to WETSoM 2013, the 4th International Workshop on Emerging Trends in Software Metrics. Since its start, WETSoM has attracted a blend of academic and industrial researchers, creating a stimulating atmosphere to discuss the progresses of software metrics. A key motivation for this workshop is the low impact that software metrics still has on current software development, raising the need for empirically evaluating the effectiveness of existing metrics, as well as to identify directions for development of new metrics.

Recent empirical work has shown that some of the most frequently applied Java-based refactorings relate to the manipulation of code conditionals and flags. The logic of such code is often complex and difficult to test regressively. One open research issue thus relates to the fault-proneness profiles of classes where these refactorings have been applied, vis-a-vis refactorings on other classes. In this paper, we explore six releases of three Eclipse projects and the faults in the refactored classes of those releases. We explore four specific conditional-based refactorings and the supposition that: classes where these four refactorings have been applied will tend to have relatively higher fault incidences because of the inherent complexity of the embedded logic given by the constructs they operate on. Results showed that one of the four refactorings in particular had been applied to classes with higher fault profiles - the `Replace Nested Conditional with Guard Clauses' refactoring. Some evidence that the `Remove Control Flag' refactoring had also been applied to relatively highly fault-prone classes was found. Relative to other types of refactoring, the result thus suggests that these two effectively signpost fault-prone classes.

Several Content Management Frameworks (CMF), either open source or with a commercial license, are available to help the publication of huge amounts of information and to develop Web applications. Unfortunately, developing Web applications through a CMF is not exempt from cost and time overruns, as in traditional software projects, and currently there is no estimation model able to adequately measure the effort of Web application development. This work presents a new methodology for estimat­ing the effort of Web applications developed with a Content Management Framework (CMF). We present the new key elements for analysis and planning, needed to define every important step in developing a Web application through a CMF. Using those elements, it is possible to estimate the effort needed to build such an ap­plication in man-days. We also present the experimental validation of the proposed methodology per­formed on a 9-project dataset, provided by three different Italian software companies.

One of the goals of Software Engineering is to reduce, or at least to try to control, the defectiveness of software systems during the development phase. The aim of our study is to analyze the relationship between micro patterns (introduced by Gil and Maman) and faults in a software system. Micro patterns are similar to design patterns, but their characteristic is that they can be identified automatically, and are at a lower level of abstraction with respect to design patterns. Our study aims to show, through empirical studies of open source software systems, which categories of micro patterns are more correlated to faults. Gil and Maman demonstrated, and subsequent studies confirmed, that 75% of the classes of a software system are covered by micro patterns. In our study we also analyze the relationship between faults and the remaining 25% of classes that do not match with any micro pattern. We found that these classes are more likely to be fault-prone than the others. We also studied the correlation among all the micro patterns of the catalog, in order to verify the existence of relationships between them.

The use of Open Source Content Management System (CMS) on the Web is increasing thanks to the flexibility provided by these systems and the semplification of the management operations. The use of CMS is simple for non programming experts. Many Public Administrations have adopted Open Source CMS for their websites, greatly reducing operating costs and ensuring scalability, advanced performance and privacy to the users. A special opportunity for a case study are the Italian municipalities. In fact the Italian Government, since January 2011, has required all municipalities to develop a website publishing all the public acts and everything related to the citizen-municipality communication (information regarding office hours, salaries of public employees, news and so on). Our study aims to quantify through empirical studies, the use of Open Source CMS in Italian municipalities websites in response to government regulations. Our results show that the number of Italian Public Administrations that use Open Source CMS is increasing, and our case study highlights how the adoption of Open Source CMS has increased about 5% in a year, leading to the 21.2% the percentage of Open Source CMS, with respect to the 15.8% registered in 2011.

The aim of refactoring is to reduce software complexity and hence simplify the maintenance process. In this paper, we explore the impact of refactorings on "FanIn" and "FanOut" coupling metrics through extraction of refactoring data from multiple releases of five Java open-source systems, We first considered how a single refactoring modified these metric values, what happened when refactorings had been applied to a single class in unison and finally, what influence a set of refactorings had on the shape of Fan In and Fan Out distributions. Results indicated that, on average, refactored classes tended to have larger FanIn and Fan Out values when compared with non-refactored classes. Where evidence of multiple (different) refactorings applied to the same class was found, the net effect (in terms of FanIn and Fan Out coupling values) was negligible.

We present a study of the effectiveness of estimating web application development effort using Function Points and Web Objects methods, and a method we propose - the Revised Web Objects (RWO). RWO is an upgrading of WO method, aimed to account for new web development styles and technologies. It also introduces an up-front classification of web applications according to their size, scope and technology, to further refine their effort estimation. These methods were applied to a data-set of 24 projects obtained by Datasiel spa, a mid-sized Italian company, focused on web application projects, showing that RWO performs statistically better than WO, and roughly in the same way as FP.

A software system can be associated to a graph - called software network - whose nodes are the software modules (for instance, the classes in Object-oriented systems), and edges are the dependencies between modules. A recent paper demonstrated that the structure of software networks is also self-similar under a length-scale transformation, and calculated their fractal dimension using the "box counting" method. In this paper, we focus on describing and evaluating alternative approaches for the computation of the fractal dimension of networks. We show that a Merge Algorithm is the most efficient, while Simulated Annealing is the most accurate. However, the Greedy Coloring algorithm, based on the equivalence of the box counting problem with the graph coloring problem, looks the best compromise, having speed comparable to MA, and accuracy comparable with SA.

We suggest that we need a fundamentally different philosophy and a concept for how organisations are led and managed. We believe that it is time to challenge the traditional management myths. The main goal of Beyond Budget- ing is not get rid of budgets. The budget must go, but it is more the budgeting mindset we need to get rid of, because it represents the old thinking that needs to be changed. Based on the works of The Beyond Budgeting Round Table, we review a set of 12 principles for a new style of contemporary leadership and management.

This paper compares the effectiveness of Function Points and Web Object analysis to estimate the development effort of Web applications. The empirical study is performed on a set of industrial projects carried on in an Italian software company. Starting from original requirements and estimates, carried on using FP analysis, we compute the Web Objects analysis of the same requirements, and compare the results of the two approaches. We also assess the relative effectiveness of FP and WO using post-mortem data about the actual effort taken to develop the studied systems.

The Tobin tax is a solution proposed by many economists for limiting the speculation in foreign exchange and stock markets and for making these markets stabler. In this paper we present a study on the effects of a transaction tax on one and on two related markets, using an artificial financial market based on heterogeneous agents. The microstructure of the market is composed of four kinds of traders: random traders, fundamentalists, momentum traders and contrarians, and the resources allocated to them are limited. In each market it is possible to levy a transaction tax. In the case of two markets, each trader can choose in which market to trade, and an attraction function is defined that drives their choice based on perceived profitability. We performed extensive simulations and found that the tax actually increases volatility and decreases trading volumes. These findings are discussed in the paper.

Can research projects be agile? In this paper we describe our proposal of applying Scrum for the management of an European research project aimed at developing an agent-based software platform for European economic policy design. The use of an agile, adaptive methodology is justified because successful research projects are complex, unstable processes, that should be continuously adapted along their way. We describe in detail the roles, artifacts and practices of the proposed process, and the first steps of its adoption.

Financial prices have been found to exhibit some universal characteristics1,2,3,4,5,6 that resemble the scaling laws characterizing physical systems in which large numbers of units interact. This raises the question of whether scaling in finance emerges in a similar way — from the interactions of a large ensemble of market participants. However, such an explanation is in contradiction to the prevalent ‘efficient market hypothesis’7 in economics, which assumes that the movements of financial prices are an immediate and unbiased reflection of incoming news about future earning prospects. Within this hypothesis, scaling in price changes would simply reflect similar scaling in the ‘input’ signals that influence them. Here we describe a multi-agent model of financial markets which supports the idea that scaling arises from mutual interactions of participants. Although the ‘news arrival process’ in our model lacks both power-law scaling and any temporal dependence in volatility, we find that it generates such behaviour as a result of interactions between agents.

In the past thirty years, options have become an important financial instrument, and now they account for a substantial percentage of total trading activity. From a research perspective, a lot of research have been carried out about the theoretical computation of option prices, starting from the seminal works of Black and Scholes (1973) and Merton (1973). Several researchers also examined the issue of to which extent options interact with their underlying stocks, and in particular their possible effects on stock returns and volatility, and on the overall quality of the underlying security market.

Team work is defined by different factors: team size, members role, interactions and communication. In Agile Methodologies communication plays a fundamental role. Some research studies have found that the involvement of team members in a project also depends on the information provided. Communication also depends on the tool employed. The aim of this paper is to analyze communication among team members of the 9 most active projects on Source-forge provided of a developers' mailing list. In particular we tried to investigate how and why members post to developers' mailing list and the use that different members make of these mailing lists.

This paper analyzes the development of a project initiated by a co-located agile team that subsequently evolved into a distributed context. The project, named JAPS (Java Agile Portal System) [1], has been monitored on a regular basis since it started in January 2005, collecting both process and product metrics. Product metrics have been calculated by checking out the source code history from the CVS repository. By analyzing the evolution of these metrics, it has been possible to evaluate how the distribution of the team has impacted the source code quality.

The problem of global optimization of magnetic structures composed of solenoids is examined, using a modified simulated annealing algorithm able to deal with the functions of continuous and/or discrete variables. The algorithm is tested using a discrete problem which allows determination of the cost function for every possible configuration of the system, providing information about the pattern of the cost function with respect to design variables. Despite the difficulty of minimizing the function, the proposed algorithm was able to locate the global minimum, or a point where the cost function has a value very close to it, seven times out of a total of ten runs. The algorithm is described, and results are discussed. >

In this paper, we present an extension of the Genoa artificial stock market (GASM) (Raberto et al., 2001) that includes a limit order book as mechanism for price formation. At every time step an agent is chosen with uniform distribution to issue an order. The order can be a limit order or a market order. If the order is a limit order, it is stored in the book; if the order is a market order, a transaction occurs. Prices are formed at variable time steps, i.e., only when a market order is issued. We investigate how the new asynchronous trading mechanism affects the statistical properties of simulated prices. This computational experiment shows that the fat tails of the returns distribution can be recovered simply as a consequence of the limit order book without any additional assumption on agents' behavior.

This paper describes a simulation model that represents the first step to modeling open source software development processes. The model has been tuned using data from a real FLOSS project: Apache. The goal of our research is to show the effects of adopting TDD (Test Driven Development) on our open source simulation model. In order to introduce the TDD practice, we have only changed some parameter values in the FLOSS simulation model. In particular, the average time required to write a line of production code increases because now automated tests are also coded, the number of defects injected during coding decreases as does the debugging time to fix a single defect. The two FLOSS development models (nonTDD and TDD) have been compared, the one incorporating the agile practice of Test Driven Development yielding better results in terms of code quality (defects/Kloc).

In recent years Extreme Programming and Agile Methodologies are becoming very popular among academics and practitioners of software engineering. In order to create a knowledge base on XP and agile methodologies, a common standard for process data representation is needed. This standard can also be used for interchanging data among different tools supporting XP projects. In this paper we present XMI as a possible solution to this problem. We show the advantages of XMI for XP project data collection and interchange. XMI is an OMG standard for modelling data object semantics in XML syntax. It integrates XML and UML and requires the definition of a model for data that must be interchanged. In this context we have defined a UML model for an XP project. The XP project model consists of a set of UML classes diagrams representing the XP project entities, their properties and relationships. The model can be easily extended to other agile methodologies. We used this model for exporting process data from XPSwiki, a tool for XP project management and for process data collection.

We describe the Extreme Programming Ontology (XPO), a formal model specifying the main concepts used in the extreme programming methodology and their properties. XPO's modular structure was developed using the usual normative top down approach to software engineering process modeling. It relies on a set of core components rooted in three main concepts: organisational role, product and phase. Besides being useful for indexing relevant documents and XP artifacts such as user stories and Wiki pages, XPO is aimed at being a sound basis for nonintrusive analysis of agile processes, mining process data about programmers activity and repositories content in order to extract new concepts potentially identifying critical factors in agile software development. Extension to XPO are also discussed, including other agile methodologies and more general software engineering concepts.

Fast algorithms for calculating the discrete Hartley transform and the Fermat number transform (FNT) are discussed from an architectural point of view. Several systolic architectures for the real-time computation of these transforms are presented. In particular, the cascade architecture for computing the FNT with the decimation-in-time algorithm is presented. >

A very versatile algorithm for the design of finite-wordlength filters is described. It is a simulated annealing algorithm, derived directly from the simulated annealing algorithm for functions of continuous variables which searches over discrete values of the filter coefficients. It has very fast development time and produces filters with good performances. Its only drawback is a very long execution time. Three examples of filter design are included. >

The discrete Hartley transform (DHT) is a real-valued transform closely related to the discrete Fourier transform (DFT) of a real-valued sequence. Several fast algorithms for the computation of the DHT (FHTs) have been proposed. A new cascade circuit for computing the DHT is presented in two versions, which implement, respectively, the radix-2 decimation-in-time and decimation-in-frequency FHT algorithms. The circuit makes use of CORDIC processors and allows an easy computation of the DFT, the amplitude and phase spectra, and the cyclic convolution and correlation of two sequences. Some architectures to perform such operations are also presented. >

A digital implementation of a multilayer neural network model that has backpropagation as its learning algorithm is presented. This architecture is characterized by a set of elementary processors (neurons) and has the form of a linear sequence, where every processor communicates only with its two nearest neighbors. A sophisticated control of data exchange among neurons, by means of two data buses, ensures full pipelining in the forward mode. The proposed architecture is very flexible since, having only local connections, it can be easily expanded by simply adjoining more processors to it. Moreover, it can be programmed in terms of number and width of layers. >

The authors present a systolic circuit for computing a fast algorithm performing the discrete Hartley transform (DHT). The proposed architecture employs a systolic elevator concept and CORDIC processors. The elevator assures local communications in the proposed algorithm, and the CORDIC processor makes it possible to enhance processing speed and exploit parallelism. The architecture appears to be regular and, therefore, very attractive for VLSI realizations. The computational cost necessary for computing the DFT (discrete Fourier transform) is also discussed with respect to other architectures. >