Michael Schmitt

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We synthesize data on all known extant and fossil Coleoptera family-group names for the first time. A catalogue of 4887 family-group names (124 fossil, 4763 extant) based on 4707 distinct genera in Coleoptera is given. A total of 4492 names are available, 183 of which are permanently invalid because they are based on a preoccupied or a suppressed type(More)
In a great variety of neuron models, neural inputs are combined using the summing operation. We introduce the concept of multiplicative neural networks that contain units that multiply their inputs instead of summing them and thus allow inputs to interact nonlinearly. The class of multiplicative neural networks comprises such widely known and well-studied(More)
We propose a mechanism for unsupervised learning in networks of spiking neurons which is based on the timing of single firing events. Our results show that a topology preserving behavior quite similar to that of Kohonen's self-organizing map can be achieved using temporal coding. In contrast to previous approaches, which use rate coding, the winner among(More)
Fast and frugal heuristics are well studied models of bounded rationality. Psychological research has proposed the take-the-best heuristic as a successful strategy in decision making with limited resources. Take-the-best searches for a sufficiently good ordering of cues (or features) in a task where objects are to be compared lexicographically. We(More)
Spiking neurons are models for the computational units in biological neural systems where information is considered to be encoded mainly in the temporal patterns of their activity. In a network of spiking neurons a new set of parameters becomes relevant which has no counterpart in traditional neural network models: the time that a pulse needs to travel(More)
Ontologies are viewed as increasingly important tools for structuring domains of interests. In this paper we propose a reference ontology of business models using concepts from three established business model ontologies; the REA, BMO, and e3-value. The basic concepts in the reference ontology concern actors, resources, and the transfer of resources between(More)
Computations by spiking neurons are performed using the timing of action potentials. We investigate the computational power of a simple model for such a spiking neuron in the Boolean domain by comparing it with traditional neuron models such as threshold gates (or McCulloch–Pitts neurons) and sigma-pi units (or polynomial threshold gates). In particular, we(More)
Networks of spiking neurons are very powerful and versatile models for biological and artificial information processing systems. Especially for modelling pattern analysis tasks in a biologically plausible way that require short response times with high precision they seem to be more appropriate than networks of threshold gates or models that encode analog(More)
In this paper we discuss the problem of how to go from a business model to a process model in a systematic way. Business models are economic models used for business analysis, while process models capture low-level business activities and their coordination. We propose a method that starts with a business model where the main actors and their relationships(More)