DSpace dijital arşiv sistemi toplar, depolar, dizinler, korur ve dijital araştırma materyallerini dağıtmaya aracılık eder. http://belgelik.isikun.edu.tr:8080/xmlui 2026-06-17T00:50:10Z 2026-06-17T00:50:10Z http://belgelik.isikun.edu.tr/xmlui/handleiubelgelik/7296 2026-06-11T19:51:50Z 2026-05-25T00:00:00Z

Işık Üniversitesi 2026 Mezunlarını Uğurladı Işık Üniversitesi 2025-2026 Akademik yılı mezuniyet korteji ve töreni haber erişimidir.

2026-05-25T00:00:00Z http://belgelik.isikun.edu.tr/xmlui/handleiubelgelik/7295 2026-06-11T19:35:56Z 2026-06-10T00:00:00Z

Seçmen mutlak butlan sonrası CHP hakkında ne düşünüyor? Işık Üniversitesi Uluslararası İlişkiler Bölüm Başkanı Prof. Dr. Seda Demiralp'in Medyascope TV kanalında yayınlanan programa konuk olduğu videonun erişimidir.

2026-06-10T00:00:00Z Hasanoğlu, Elman http://belgelik.isikun.edu.tr/xmlui/handleiubelgelik/7294 2026-06-11T10:56:33Z 2026-06-01T00:00:00Z

Oktay Veliev, Multidimensional Periodic Schrödinger Operator (Perturbation Theories in High Energy Regions and Their Applications) Hasanoğlu, Elman Book Review: Oktay Veliev, Multidimensional Periodic Schrödinger Operator (Perturbation Theories in High Energy Regions and Their Applications). Springer, Switzerland, 424 pp., 2024, Springer Tracts in Modern Physics, STMP, Vol. 291.

2026-06-01T00:00:00Z Reddy, B. Bhaskar Kumari Chilukuri, Raja Tummala, Anil Chowdary Rao Musala, Venkateswara Kakarla, Hari Kishore Manoharan, Kavitha http://belgelik.isikun.edu.tr/xmlui/handleiubelgelik/7293 2026-06-11T06:21:08Z 2026-06-01T00:00:00Z

A unified spectral filter framework for ill-posed linear operator equations in Hilbert spaces Reddy, B. Bhaskar; Kumari Chilukuri, Raja; Tummala, Anil Chowdary; Rao Musala, Venkateswara; Kakarla, Hari Kishore; Manoharan, Kavitha Regularization is useful for stable recovery in inverse problems with ill-posed linear operator equations in Hilbert spaces because small perturbations in data can make problems highly unstable. Tikhonov regularization, truncated singular value decomposition, and iterative polynomial filtering, classical methods, have been understood from singular value decay and the Picard condition. However, most literature analyses convergence, parameter choice, and saturation from separate perspectives. This study fills the gap by constructing a unified spectral filter framework that integrates bias–variance decomposition, polynomial and exponential decay, convergence rate analysis, and stabilityconsistent parameter choice frameworks, including the discrepancy principle and the Lcurve criterion. To enhance saturation control and qualification, we propose extensions to fractional and generalized spectral filters. In the severely ill-posed setting, we identify logarithmic convergence barriers with the inductive method, thereby exposing accuracy limits that exist independently from filter design. The findings are directly applicable to stable inversion and are operator theoretically sound for real-world applications, including medical imaging, geophysical reconstruction, signal processing, and data-driven recovery of ill-conditioned systems.

2026-06-01T00:00:00Z