In this paper the entropy of a flexible phase (FP) medium (referred as FP entropy) emerges from a novel linger thermo theory (LTT) and then used in a biological lifespan study. LTT is the `dynamic metrics' dual of the `stationary metrics' latency information theory (LIT). These two nascent theories are synergistic time/space designs of the universal cybernetics duality (UC duality), first identified in linear quadratic Gaussian (LQG) control in 1978. While LIT has already yielded outstanding solutions for high-performance radar, LTT has done the same for biological lifespan, with both holding US patents. The FP entropy equation is found here subject to a constant internal mass-energy constraint of LTT that reflects actual gravitational/non-gravitational interactions of atoms or molecules. Moreover, this approach is revealed to contain a degrees of freedom (DoF) coupling constant that when multiplied by the heat capacity of liquid water at 310 K in thermal equilibrium accurately models the heat capacity of the human medium in its non-equilibrium thermal state. The use of the DoF coupling constant mechanism has been found to result in outstanding theoretical adult lifespan predictions that are directly linked to an individual's heat capacity. These sensible results compel the view that the FP entropy approach will find broad use in future biophysical chemistry of lifespan studies.

Lingerdynamics is thermodynamics' time dual that inherently surfaced from latency information theory (LIT), which is itself a nascent universal guidance theory for efficient system designs. This paper reveals two novel lingerdynamics ectropies that are the time duals of two thermodynamics entropies, one of which is also novel. The classical thermodynamics source-entropy (TSE) of information-sources and the novel thermodynamics retainer-entropy (TRE) of information-retainers are thermodynamics', while the lingerdynamics processor-ectropy (LPE) of information-processors and the lingerdynamics mover-ectropy (LME) of information-movers are lingerdynamics'. An important finding of this paper is the discovery that the 2ndlaw of thermodynamics must be enhanced to state that the universe's two TSE and TRE entropies, not just the TSE, must continuously increase. Another finding is the 2ndlaw of lingerdynamics that states that the universe's two LPE and LME ectropies continuously increase. Guided by these results a new lifespan LIT duality theory for both living and non-living systems is revealed and the gravitational and electrical forces shown to be emergent TRE entropic forces. Finally LIT leads us to the theory that the universe's unexplained dark-energy and dark-matter can be explained as a motion-vacuum-energy/retention-black-hole-gravity LIT duality.

A novel practical and theoretical foundation for signal processing, named processor coding, is advanced as the computational time compression dual of source coding. Source coding is concerned with signal source memory space compression while processor coding is with signal processing computational time compression. Since source coding and processor coding solutions are characterized by compression designs, their combined use is given the name compression-designs (referred as Conde in short). A compelling and pedagogically appealing descriptive diagram of Conde is also given which highlights its remarkable successful application to knowledge-aided (KA) airborne moving target indicator (AMTI) radar subjected to severely taxing environmental disturbances.

Minimum mean squared error (MMSE) predictive-transform (PT) source coding is integrated with subband compression to further improve the performance of low bit rate MMSE PT source coders. A desirable byproduct of the advanced scheme is that the incorporation of joint optimum prediction and transformation from subband to subband is ideally suited to its integration with JPEG2000 to yield even higher compression levels while producing an outstanding objective as well as subjective visual performance.

This paper presents a novel accelerated predictive-transform (APT) modeling methodology for use in compression. The APT scheme is illustrated with a monochrome 2D image compression application yielding very promising results. For example, when the Lena image is compressed to 0.056 bits per pixel and the pixel blocks are of dimension 16×16, it is shown that both the design and implementation computational complexity of the prior predictive-transform (PT) modeling art is improved by a factor of 12 without any loss in the visual quality of the compressed image. The APT methodology can also be used in other application areas such as estimation; detection, identification, channel and source integrated coding, and control and other related areas.

A superimposed (Super for short) minimum mean squared error (MMSE) predictive-transform (PT) residual vector quantization (RVQ) coder is introduced in this paper. The Super MMSE PT-RVQ coder arises as a straight forward generalization of a recently offered MMSE PT-RVQ coder and addresses in a simple and elegant fashion the noticeable blocking artifacts that are encountered with the MMSE PT-RVQ coder when operating at very low bit rates. The technique is illustrated by compressing five monochrome test images obtained from the JPEG suitcase at compression ratios as high as 229 to 1 or equivalently at bit rates as low as 0.035 bps. It is found that for all test images the Super PT-RVQ coder generally outperforms the perceptual quality and peak SNR derived with the Said and Pearlman wavelet algorithm.

This work investigates a new compression scheme that incorporates rate-constrained residual vector quantization (RVQ) of the transform coefficient error vectors arising in a minimum mean squared error (MMSE) predictive-transform (PT) methodology. The proposed technique that we call predictive-transform residual vector quantization (PTRVQ) exploits the correlation between neighboring blocks by predicting the transform coefficients of each block using information from previously encoded blocks. PTRVQ, therefore, exploits both the intra- and inter-block correlation as well as employs dimensionality reduction in the transform domain in order to generate a highly compact code. Experimental results obtained with several standard monochrome images and compression ratios as high as 135:1 demonstrate quite noticeable improvements of the reconstructed images in both perceptual quality and peak signal to noise ratio (PSNR). The PSNR improvements are as high as 1.4 dB over a wavelet based coder.

It is shown that a recently offered minimum MSE linear predictive transform (LPT) coding formulation inherently leads to a simple and highly efficient continuous amplitude (analog) data compression algorithm. In the proposed scheme only the most energetic unquantized coefficient errors produced by the encoder are transmitted to effect the desired analog data compression. The technique is illustrated with NTSC monochrome images having a bandwidth of 3.6 MHz, and a communication channel characterized by additive zero mean white noise. It is demonstrated that when half of the coefficient errors are transmitted, that is the bandwidth of the transmitted coefficient error signal has been reduced from 3.6 MHz to 1.8 MHz, the reconstructed signal is very close to SNR and visual performance to that obtained when all the coefficient errors are transmitted.>

A unified approach to optimum digital signal modeling, coding, estimation, and control is outlined. The origins of the proposed technique reside in a minimum-mean-square-error predictive transform (PT) coding formulation which yields a decoder that is a whitening PT model of the source whose output is to be encoded. This PT decoder is integrated with Kalman estimation (prediction, filtering and smoothing) as well as linear quadratic Gaussian control to produce a comprehensive approach to estimation and control that directly addresses the signal modeling problem. An additional bonus of the proposed unified approach to optimum digital signal processing is that a transformation mechanism arises which leads to significant design and implementation simplifications when the dimension of the signal is large. These ideas are illustrated with a 2D monochrome image application, where it is found that the design and implementation requirements of a PT smoother are often much less than those of a Kalman smoother with strictly similar performance. Specifically, the design computational burden is often improved by a factor greater than four and the implementation complexity burden by a factor close to four.>

The transmission of NTSC composite color images over digital communication channels is generally accomplished by coding the less correlated component signal, YIQ. Unless the video source is available, the component signals are separated from the composite signal by using comb-filters. Comb-filtering is generally performed in the temporal domain. This paper shows that by properly sampling the NTSC composite color signal at four times the color subcarrier, the Walsh-Hadamard transform acts like a comb filter and separates the YIQ components of the composite signal. The YIQ components will be mapped into specific locations of the coefficient matrix.

Predictors operating on video signals sampled at six times the color subcarrier(6f_{c})have been investigated and compared with predictors operating at three times the color subcarrier(3f_{c}). When the best6f_{c}predictor is used with an adaptive delta modulator (ADM) step size generator, the resulting pictures are similar in quality to3f_{c}predictors operating with a four-level adaptive DPCM quantizer. An ADM coder was implemented in real time. The coder used between 24 and 34 IC's, depending upon the algorithm, and fits on a single 9 in × 6 in PC board. The transmission rate is 21.4 Mbits/s.

This paper describes a one-stage look-ahead algorithm for adaptive delta modulators. The algorithm does not require the calculation of two encoding paths nor does it require the decision circuitry to choose the optimum path.