King of the Renaissance: Art and Politics at the Neapolitan Court of Ferrante I, 1458-1494

In the second half of the fifteenth century, King Ferrante I of Naples (r. 1458-1494) dominated the political and cultural life of the Mediterranean world. His court was home to artists, writers, musicians, and ambassadors from England to Egypt and everywhere in between. Yet, despite its historical importance, Ferrante’s court has been neglected in the scholarship. This dissertation provides a long-overdue analysis of Ferrante’s artistic patronage and attempts to explicate the king’s specific role in the process of art production at the Neapolitan court, as well as the experiences of artists employed therein. By situating Ferrante and the material culture of his court within the broader discourse of Early Modern art history for the first time, my project broadens our understanding of the function of art in Early Modern Europe. I demonstrate that, contrary to traditional assumptions, King Ferrante was a sophisticated patron of the visual arts whose political circumstances and shifting alliances were the most influential factors contributing to his artistic patronage. Unlike his father, Alfonso the Magnanimous, whose court was dominated by artists and courtiers from Spain, France, and elsewhere, Ferrante differentiated himself as a truly Neapolitan king. Yet Ferrante’s court was by no means provincial. His residence, the Castel Nuovo in Naples, became the physical embodiment of his commercial and political network, revealing the accretion of local and foreign visual vocabularies that characterizes Neapolitan visual culture.

Sparse Signal Representation in Digital and Biological Systems

Theories of sparse signal representation, wherein a signal is decomposed as the sum of a small number of constituent elements, play increasing roles in both mathematical signal processing and neuroscience. This happens despite the differences between signal models in the two domains. After reviewing preliminary material on sparse signal models, I use work on compressed sensing for the electron tomography of biological structures as a target for exploring the efficacy of sparse signal reconstruction in a challenging application domain. My research in this area addresses a topic of keen interest to the biological microscopy community, and has resulted in the development of tomographic reconstruction software which is competitive with the state of the art in its field. Moving from the linear signal domain into the nonlinear dynamics of neural encoding, I explain the sparse coding hypothesis in neuroscience and its relationship with olfaction in locusts. I implement a numerical ODE model of the activity of neural populations responsible for sparse odor coding in locusts as part of a project involving offset spiking in the Kenyon cells. I also explain the validation procedures we have devised to help assess the model's similarity to the biology. The thesis concludes with the development of a new, simplified model of locust olfactory network activity, which seeks with some success to explain statistical properties of the sparse coding processes carried out in the network.