The landscape of signal processing books is quite populated, and it is a tall order to produce a new book that can constructively add to this landscape. This book not only accomplishes this but also stands out for its distinct, consistent, and strong personality. The book’s identity starts from a presentation that is faithful to its title since the topics covered in this book are thorough in explaining the foundations of signal processing. However, foundations can be built in many ways and with different materials. The distinct element in this book is that these foundations are built based on the use of Hilbert space geometry, which allows extending Euclidean geometric insights to signals. As such, the geometry of Hilbert spaces forms the common thread across the multiple topics explained in the book. This allows for a presentation where the topics, such as Fourier representations, sampling, interpolation, approximation, compression, and filter design, can be seamlessly unified across finite dimensions, discrete time, and continuous time.