Showing papers by "Uwe Meyer-Baese published in 2014"
01 Jan 2014
TL;DR: Many of the principals the authors have discussed so far like filtering or FFT can be directly extended to 2D and 3D processing and the discussion of these algorithms short.
Abstract: Image and video processing can be considered as a generalization of the one dimensional (1D) signal processing to 2D and 3D, respectively. In image processing we add a second coordinate in the y direction and for video processing we would add a temporal a.k.a. spatial dimension. Many of the principals we have discussed so far like filtering or FFT can be directly extended to 2D and 3D processing and we will keep the discussion of these algorithms short.
22 citations
01 Jan 2014
TL;DR: The most common digital filter is the linear time-invariant (LTI) filter as discussed by the authors, which interacts with its input signal through a process called linear convolution, denoted by y = f * x where f is the filter impulse response, x is the input signal, and y is the convolved output.
Abstract: Digital filters are typically used to modify or alter the attributes of a signal in the time or frequency domain. The most common digital filter is the linear time-invariant (LTI) filter. An LTI interacts with its input signal through a process called linear convolution, denoted by y = f * x where f is the filter’s impulse response, x is the input signal, and y is the convolved output.
3 citations
TL;DR: The two main standard techniques that can be applied to the analysis of large scale phosphoproteomics data sets are data‐driven or exploratory techniques based on a statistical model and topology‐driven methods that analyze the signaling network from a dynamical standpoint.
Abstract: The interpretation of phosphoproteomics data sets is crucial for generating hypotheses that guide therapeutic solutions, yet not many techniques have been applied to this type of analysis. This paper intends to give an overview about the two main standard techniques that can be applied to the analysis of these large scale data sets. These are data-driven or exploratory techniques based on a statistical model and topology-driven methods that analyze the signaling network from a dynamical standpoint. While employing different paradigms, these algorithms will detect unique "fingerprints" by revealing the intricate interactions at the proteome level and will support the experimental environment for novel therapeutics for many diseases.
3 citations
01 Jan 2014
TL;DR: The fundamentals of IIR filter design will be developed, namely Butterworth, Chebyshev I and II, and elliptic filters, which will review the four most important classes of these analog prototype filters.
Abstract: In this chapter, the fundamentals of IIR filter design will be developed. The traditional approach to the design of IIR filters involves the transformation of an analog filter, with defined feedback specifications, into the digital domain. This is a reasonable approach, mainly because the art of designing analog filters is highly advanced, and any standard tables are available, i.e., [99]. We will review the four most important classes of these analog prototype filters in this chapter, namely Butterworth, Chebyshev I and II, and elliptic filters.
2 citations
TL;DR: It is shown that the number of prime factors of the constants is key information to extend the current lower bounds in certain cases that have not yet been exposed.
Abstract: This paper presents an extension to the theoretical lower bounds for the number of adders and for the adder depth in multiplierless single constant multiplications (SCM). It is shown that the number of prime factors of the constants is key information to extend the current lower bounds in certain cases that have not yet been exposed. Additionally, the hidden theoretical lower bound for the number of adders required to preserve the minimum adder depth is revealed.
2 citations
01 Jan 2014
TL;DR: In this chapter, two typical examples will illustrate decimation and interpolation in multirate DSP systems, polyphase notation is introduced, and some efficient decimator designs are discussed.
Abstract: A frequent task in digital signal processing is to adjust the sampling rate according to the signal of interest. Systems with different sampling rates are referred to as multirate systems. In this chapter, two typical examples will illustrate decimation and interpolation in multirate DSP systems. We will then introduce polyphase notation, and will discuss some efficient decimator designs. At the end of the chapter we will discuss filter banks and a quite new, highly celebrated addition to the DSP toolbox: wavelet analysis.
1 citations